Tower crane amplitude variation-rotation linkage self-adaptive control method for high wind load environment

Abstract

The invention relates to the technical field of automatic control, in particular to a tower crane variable amplitude-rotation linkage self-adaptive control method oriented to a high wind load environment. The method comprises the following steps: step 1, acquiring an actually measured average wind speed at the height of the tower crane so as to determine a wind-induced coupling torque acting on a rotating shaft of the tower crane; 2, real-time equivalent rotational inertia generated by the dead weight of the cantilever crane, the suspended load mass and the relative position of the cantilever crane is calculated in real time; step 3, obtaining an original variable-amplitude torque instruction output by a variable-amplitude motor of the tower crane; and step 4, utilizing the rotating shaft to couple the rotational inertia so as to update the rotation angular velocity set value of the tower crane in the next control period in real time, and completing the amplitude variation-rotation linkage self-adaptive control of the tower crane. According to the invention, the safety, precision and continuous operation capability of the tower crane under complex construction conditions are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of automatic control, and in particular relates to a tower crane luffing-slewing linkage adaptive control method for a high wind load environment. Background Art

[0002] During the operation of tower cranes, wind load disturbance is always a key factor affecting their structural stability and control accuracy. Especially in high wind load environments, complex wind field characteristics such as sudden changes in wind speed, gust pulsation and air flow shear will have a strong impact on the tower crane's boom system and hoisting system, resulting in a series of safety hazards such as increased hoisting swing, delayed attitude response and even structural overload. With the increasing demand for high-risk and high-wind projects such as super-high-rise buildings, offshore wind power, and ultra-high voltage construction, the problem of tower cranes' wind load adaptability in harsh environments has become increasingly prominent, and there is an urgent need to upgrade and optimize traditional tower crane control systems from the control strategy level. Most of the existing tower crane control systems adopt a modular design, that is, the luffing mechanism and the slewing mechanism are independently controlled according to their own dynamic models. The typical control strategy is mainly based on PID regulation, supplemented by mechanisms such as speed feedforward or current compensation, which can achieve basic trajectory tracking and operation response under normal working conditions. However, when wind loads act significantly, this type of control system generally faces three problems: First, there is a lack of real-time recognition capability for wind-induced disturbances. Traditional control systems usually model external disturbances as small disturbances or white noise types with constant mean values, while ignoring the non-stationary characteristics of the real wind field. Especially in high wind load environments where gusts and vortex structures frequently occur, wind speed changes are not only sudden, but also have strong spatial correlation and time asynchrony. Single-point wind measurement devices cannot provide effective wind speed distribution information covering the entire boom system. Since the control system cannot obtain complete data reflecting the spatial characteristics of the wind field, there is a response lag between the control command and the actual disturbance, which is prone to control error amplification and even torque command instability. Secondly, existing systems generally use fixed structural parameters for dynamic modeling, which fails to dynamically adapt to changes in structural loads. During the operation of the tower crane, the hoisting mass, boom length and amplitude angle are often in a changing state, and these factors directly affect the rotational inertia and coupling torque distribution of the entire machine. In traditional control models, inertia parameters are usually determined during the factory calibration stage and are no longer updated during operation. This static modeling method cannot reflect the dynamic structural response during the actual operation process, especially when the load changes greatly or the wind disturbance is severe. The original model will have large errors, resulting in reduced control accuracy and even abnormal mechanism response. Summary of the invention

[0003] The main object of the present invention is to provide a luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments, which improves the safety, accuracy and continuous operation ability of tower cranes under complex construction conditions.

[0004] To solve the above problems, the technical solution of the present invention is realized as follows: A luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments, the method comprising: Step 1: Obtain the measured average wind speed at the height where the tower crane is located, and combine the slewing angular velocity, boom length, luffing angle and slewing angle of the tower crane to calculate the windward projected area and relative wind speed of the boom, so as to determine the wind-induced coupling moment acting on the slewing shaft of the tower crane; Step 2: Calculate the vertical projection distance from the slewing center of the tower crane to the load according to the inherent moment of inertia of the tower crane, the self-weight of the boom, the load mass, the boom length, the luffing angle and the slewing angle, and calculate the real-time equivalent moment of inertia generated by the self-weight of the boom, the load mass and their relative positions in real time; Step 3: Obtain the original luffing moment command for the output of the luffing motor of the tower crane through the sum of the product of the real-time equivalent moment of inertia and the luffing angular acceleration command, the viscous damping effect of the luffing mechanism, the gravity moment generated by the load mass, and the projection of the wind-induced coupling moment in the luffing direction; Step 4: Use the coupled moment of inertia of the slewing shaft to convert the projection of the calculated wind-induced coupling moment in the slewing direction, the overturning component of the gravity of the load mass on the slewing shaft, and the kinetic energy coupling effect caused by the linkage of the luffing angular velocity and the slewing angular velocity into a correction amount of the slewing angular velocity, so as to update the slewing angular velocity setting value of the tower crane in the next control cycle in real time, and complete the luffing-slewing linkage adaptive control of the tower crane.

[0005] Further, in Step 1, ultrasonic anemometers are respectively arranged near the tip of the tower crane boom, at the position of the tower cap and above the tower body base at a predetermined multi-layer height to synchronously collect the incoming flow wind speed, wind direction and turbulence pulsation intensity as the original meteorological data; the original meteorological data is sent to the central processing unit after generating a time stamp according to a unified clock, so as to form a wind field original data set covering all measurement points in each control cycle.

[0006] Further, the central processing unit performs the following processes: implementing multi-level filtering on the original wind field data set, specifically including: using band-pass filtering to suppress low-frequency drift and high-frequency noise, using a sliding time window to smooth gust pulsations, and removing instantaneous distortion samples according to a preset anomaly detection threshold to obtain effective wind speed and effective wind direction with stable statistical characteristics; according to the real-time luffing angle, slewing angle and boom length of the tower crane, calling a coordinate transformation algorithm to decompose the effective wind speed into a tangential component consistent with the longitudinal direction of the boom and a normal component perpendicular to the boom plane; according to the boom windward projection area database, performing look-up table matching on the equivalent windward area in different postures, and combining the tangential component and the normal component with the equivalent windward area to construct a comprehensive wind load field reflecting the instantaneous aerodynamic state of the tower crane; mapping the comprehensive wind load field to the slewing axis coordinate system, and obtaining the instantaneous wind-induced coupling moment acting on the slewing axis by integral method according to the length of the acting arm from the boom to the slewing center and the centroid position of the boom; synchronously reading the slewing angular velocity and the tangential linear velocity information of the boom tip of the tower crane, and coupling and correcting the wind-induced coupling moment in combination with the real-time wind direction deviation angle to reflect the real-time influence of the slewing motion on the relative wind speed.

[0007] Further, step 2 specifically includes: reading the inherent moment of inertia of the tower body and the slewing platform, the self-weight of the boom, the boom length, and the geometric positions of the centroid of the boom and the slewing center as a set of static design parameters, and performing a one-time locking on the set of static design parameters based on the factory calibration report; obtaining the real-time value of the load mass and the instantaneous position of the load in the longitudinal direction of the boom, and combining the luffing angle and slewing angle information shared in step 1 to perform coordinate transformation on the vertical projection distance of the load in the slewing plane and the acting arm from the boom to the slewing center, and constructing a dynamic position model of the load mass in the slewing axis coordinate system; according to the dynamic equivalent principle of the tower crane, adding the inherent moment of inertia of the tower body and the slewing platform, the self-weight of the boom and its inertia components generated by the change of the luffing angle, and the inertia contribution of the load mass at the real-time position to the slewing axis item by item, and introducing the coupling inertia cross term between the centroid of the boom and the load relative to the slewing center during the accumulation process to obtain the real-time equivalent moment of inertia.

[0008] Further, the real-time value of the load mass is obtained through a load measuring pin or a wire rope tension sensor, and the instantaneous position of the load is obtained through a luffing trolley travel encoder; the central processing unit uses the pulse feedback signal of the main hoisting drive of the tower crane and the low-frequency swing data collected by the boom tip inertial measurement unit to check the small swing angles of the load mass in the longitudinal and transverse directions, and corrects the instantaneous space coordinates of the load centroid accordingly; during the inertia accumulation process, perform exponential weighted moving average filtering on the input of the load mass position and the boom luffing angle, and remove abnormal sampling points exceeding three times the median absolute deviation range through chi-square test to improve the statistical robustness of the inertia estimation.

[0009] Furthermore, at the end of each control cycle, the central processing unit performs a least squares self-calibration operation by comparing the measured angular acceleration output by the gyroscopic angular velocity sensor with the theoretical angular acceleration predicted based on the real-time inertia model, and slightly adjusts the residuals of the boom centroid position and the load centroid position in the coordinate transformation matrix; when the change range of the real-time equivalent moment of inertia relative to the previous cycle exceeds the safety threshold, the inertia freezing logic is triggered and an inertia anomaly alarm is sent to the tower crane main controller.

[0010] Furthermore, step 3 specifically includes: the central processing unit simultaneously calls the wind-induced coupling torque determined in step 1 and the real-time equivalent moment of inertia determined in step 2 within each control cycle, and calculates the original luffing torque command output by the tower crane luffing motor based on the established tower crane luffing dynamics model to actively compensate for high wind load disturbances; the calculation process includes: forming a closed-loop error signal group containing errors, error change rates, and historical integral quantities based on the target luffing angle trajectory and the real-time measured luffing angle; generating an inertia feedforward component with the real-time equivalent moment of inertia and the desired luffing angular acceleration to cancel the uncertainty of the mass distribution change; combining the damping component obtained by filtering the luffing motor speed, the disturbance compensation amount formed by the projection of the load gravity and the wind-induced coupling torque in the luffing plane, and performing hierarchical synthesis with the closed-loop error signal group; outputting the original luffing torque command to complete the adaptive control of the luffing mechanism.

[0011] Furthermore, an integral anti-windup logic is embedded in the stage of generating the original luffing torque command, and the integral accumulation speed is limited according to preset conditions to prevent instantaneous torque overshoot caused by strong gusts; when the original luffing torque command is lower than the safety lower limit, the original luffing torque command is set to zero to avoid motor jitter in the low load area; when the original luffing torque command is higher than the safety upper limit, the peak is clipped according to a linearly decreasing curve and a potential overload risk signal is sent; the original luffing torque command after soft limiter processing is cross-checked with operating parameters such as the DC bus voltage, the temperature rise of the braking resistor, and the phase margin of the servo drive. If it is found that the braking unit is saturated or the bus voltage exceeds the limit, the energy dissipation priority strategy is triggered, and part of the potential energy feedback sequence is allocated to the slewing or hoisting drive to achieve cross-mechanism energy balance.

[0012] Furthermore, in step 4, the central processing unit uses the wind-induced coupling torque obtained in step 1, the real-time equivalent moment of inertia determined in step 2, and the original amplitude-changing torque command output in step 3 as input boundary conditions in each control cycle, and performs the following operations according to the tower crane rotation dynamics and energy conservation principle to achieve rotation stability control under high wind load environment: dispatch the projection data of the wind-induced coupling torque in the rotation direction, and perform vector-level synthesis with the overturning component converted from the load gravity in the same cycle to obtain the instantaneous synthetic torque describing the real-time external disturbance state; call the real-time The instantaneous synthetic torque is converted into the target angular acceleration by using the equivalent rotational inertia, and the actual angular velocity and angular acceleration fed back by the slewing drive are combined to form a closed-loop error signal set including the velocity deviation, acceleration deviation and historical velocity integral. According to the energy shaping idea, the coupling kinetic energy term between the amplitude variation angular velocity and the slewing angular velocity is calculated, and it is mapped into the angular velocity adjustment amount and superimposed on the velocity deviation to form a preliminary corrected angular velocity setting value, so as to update the slewing angular velocity setting value of the tower crane in the next control cycle in real time, and complete the linkage adaptive control of the amplitude variation and slewing of the tower crane.

[0013] Furthermore, the central processing unit is also equipped with an extreme wind load safety back-off control mechanism, which specifically includes: when the transient impact value monitored by the slewing acceleration sensor exceeds the structural limit threshold, it immediately enters the three-level back-off control mode, in which the first stage freezes the slewing servo angular velocity command and broadcasts a coordinated deceleration request to the variable amplitude drive module; the second stage reduces the impact of the wind-induced steep rise on the slewing system by dynamically adjusting the horizontal damping of the hook and the opening of the tower top wind baffle; in the third stage, after confirming that the wind speed and the swing amplitude of the load have fallen back to a controllable range, the freeze is gradually lifted and the closed-loop adaptive correction process is restored; during the back-off control period, the residual wind-induced coupling torque in the slewing direction is continuously calculated in a low-frequency scanning manner, and normal control is automatically re-enabled when the safety window appears.

[0014] The tower crane luffing-slewing linkage adaptive control method for high-wind load environments of the present invention has the following beneficial effects: By setting up ultrasonic anemometers arranged at multiple points and combining coordinate transformation algorithms and real-time attitude information, high-frequency perception and spatial decomposition of the instantaneous wind load state are achieved, enabling the control system to dynamically and accurately obtain the instantaneous torques exerted by wind-induced disturbances on the boom and the slewing axis. Based on this information, the central processing unit constructs a comprehensive wind load field and maps it to the slewing axis coordinate system, ensuring high responsiveness and real-time coupling in the calculation of wind-induced coupling torques. Combining the load mass, boom attitude, and real-time position relationship, the system completes the online identification of the load inertia and the adaptive correction of the boom motion inertia within each control cycle, and updates the equivalent moment of inertia model in real time, significantly improving the physical consistency and execution accuracy of the torque commands. At the same time, the present invention introduces components such as inertia feedforward, damping compensation, and disturbance projection during the generation of the luffing torque. By embedding an anti-saturation logic and a soft-limiting strategy, it effectively suppresses the instantaneous overshoot phenomenon under strong winds, reduces the motor load fluctuation, and improves the stability of the actuator. In addition, during the slewing control stage, through the dynamic integration of the wind load combined torque, slewing inertia, and kinetic energy coupling, real-time adaptive correction of the angular velocity set value is achieved, ensuring that the tower crane can still maintain a stable attitude and accurate load trajectory under sudden changes in wind speed or structural load changes. Especially when extreme wind conditions occur, the present invention has a three-level control withdrawal process, covering angular velocity freezing, structural energy consumption regulation, and control recovery mechanisms, constructing a global safety control closed-loop, and significantly enhancing the fault tolerance and robustness of the system. Overall, the present invention establishes a tightly coupled linkage logic from wind field perception, structural response, dynamic modeling to control output, solves key problems such as model lag, response lag, and execution mismatch of traditional control methods in high-wind disturbance environments, and improves the safety, accuracy, and continuous operation ability of the tower crane under complex construction conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 FIG. is a schematic flow chart of the tower crane luffing-slewing linkage adaptive control method for high-wind load environments provided by an embodiment of the present invention; Figure 2 FIG. is a test result diagram of the linkage control performance provided by an embodiment of the present invention; Figure 3 FIG. is a comparison diagram of the control effects of the luffing torque provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] To enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0017] Reference Figure 1 : A tower crane luffing-slewing linkage adaptive control method for high-wind load environments, the method comprising: Step 1: Obtain the measured average wind speed at the height where the tower crane is located, and calculate the windward projection area and relative wind speed of the jib in combination with the slewing angular velocity, jib length, luffing angle and slewing angle of the tower crane, so as to determine the wind-induced coupling moment acting on the slewing shaft of the tower crane; Step 2: Calculate the vertical projection distance from the slewing center of the tower crane to the load according to the inherent moment of inertia of the tower crane, the self-weight of the jib, the load mass, the jib length, the luffing angle and the slewing angle, and calculate the real-time equivalent moment of inertia generated by the self-weight of the jib, the load mass and their relative positions in real time; Step 3: Obtain the original luffing moment command for the output of the tower crane luffing motor through the sum of the product of the real-time equivalent moment of inertia and the luffing angular acceleration command, the viscous damping effect of the luffing mechanism, the gravity moment generated by the load mass, and the projection of the wind-induced coupling moment in the luffing direction; Step 4: Use the coupling moment of inertia of the slewing shaft to convert the projection of the calculated wind-induced coupling moment in the slewing direction, the overturning component of the gravity of the load mass on the slewing shaft, and the kinetic energy coupling effect caused by the linkage of the luffing angular velocity and the slewing angular velocity into the correction amount of the slewing angular velocity, so as to update the slewing angular velocity setting value of the tower crane in the next control cycle in real time, and complete the linkage adaptive control of the tower crane luffing-slewing.

[0018] In a high wind load environment, the essence of the dynamic control problem of tower cranes is: under the dual uncertainties of strong wind disturbances and load changes, how to coordinate two systems with coupled dynamic behaviors, namely the luffing mechanism and the slewing mechanism of the tower crane, so that the dynamic response of the entire system is neither unstable nor has rapidity and accuracy. The traditional tower crane control system mainly adopts a separate control architecture, that is, the luffing and slewing are designed with independent controllers respectively. However, in high wind load scenarios, the two are strongly coupled due to non-linear aerodynamic coupling and inertial force transmission, which in turn leads to phenomena such as "amplification of swing angle", "oscillation of suspended load", and "deviation of tip trajectory of the boom". Therefore, the method proposed in the present invention takes "physical consistency of system modeling" and "online self-adaptation of dynamic parameters" as the core. By unified modeling of wind-induced disturbances, mass distribution, drive characteristics and linkage behaviors, the luffing-slewing two mechanisms are regarded as a coupled dynamic system for control.

[0019] From the perspective of the system structure, its core principle belongs to a four-stage closed-loop link of disturbance perception - state reconstruction - torque distribution - speed regulation. The first stage is disturbance perception, which essentially constructs a physical picture of a "disturbance field driving quantity" through a real-time meteorological perception system and the boom motion state information. In this stage, the wind speed is not an independent variable, but forms a "relative wind speed field" through coupling with the tower crane motion (mainly the slewing speed and luffing attitude). After the aerodynamic projection of this wind speed field on the tower crane boom undergoes spatial direction conversion, it acts on different control objects such as the slewing axis and the luffing axis. Therefore, the wind load cannot be simply regarded as an external input disturbance, but must be involved in the state estimation. The second stage is state reconstruction, that is, the real-time calculation of the dynamic equivalent moment of inertia. This is the key link for the system to achieve "self-adaptation" because the load condition of the tower crane is not fixed, and its moment of inertia will change continuously due to factors such as the suspended load mass, luffing angle, swing amplitude of the suspended load, and position offset after being blown by the wind. If these inertia changes are not perceived and compensated, it will lead to controller parameter mismatch, overshoot or undershoot of the actuator. For this reason, the system needs to construct a real-time inertia model based on the decoupling expression of the tower crane dynamics structure and adjusted dynamically with the attitude and load state, so that the control algorithm can take into account the physical changes of the "control object" during torque distribution and improve the robustness of the controller.

[0020] The third stage is torque distribution, which means mapping the system state variables (including attitude, velocity, acceleration, inertia) and external disturbances (wind force, gravity torque) onto the drive commands together to achieve the adaptive control of the output torque of the luffing motor. The core technical principle of this stage is the "physical consistency control law": the controller is no longer based on the error feedback of a fixed model (such as traditional PID), but solves the mechanical balance according to the inertial characteristics and disturbance structure of the current system. That is to say, each frame of control command reflects the physical reality of the current system, rather than empirical adjustment or fixed gain processing. In this control structure, the generation of torque is not a response to the error, but the real force required for the mechanical response of the system state to the desired trajectory. The fourth stage is speed regulation, mainly for the slewing mechanism. This part is coupled with the luffing mechanism. Especially when the luffing acceleration changes or the wind load direction changes, the slewing shaft will feel the coupled inertial force and aerodynamic torque. The principle basis of this stage is the "momentum-energy consistency adjustment", that is, taking the equivalent moment of inertia as a reference, converting the total disturbing torque acting on the slewing shaft (wind force, gravity component, luffing linkage term) into the change of angular acceleration, and then using it to adjust the slewing angular velocity setting value of the next cycle. This adjustment is not a speed limit based on a static model, but a dynamic reconfiguration based on the momentum transfer mechanism at the current moment. Essentially, this constitutes a small-step angular momentum conservation prediction mechanism, aiming to avoid the "secondary sway" caused by inertial coupling while maintaining the control accuracy.

[0021] The key to realizing the coordinated control by this method does not lie in simply connecting the slewing and luffing controllers in series, but in introducing the mechanism of "modeling the influence of the other party's state" into the control logic, that is, considering the momentum contribution of the luffing state in the slewing control and considering the influence of the slewing speed on the relative wind speed in the luffing torque. In this way, the two originally separately controlled systems are substantially coupled through the state propagation chain, and then the controller design becomes a unified multivariable closed-loop system. This method is particularly suitable for high-wind load environments. The reason is that in scenarios with low wind speeds, the aerodynamic force accounts for a very small proportion in the energy structure of the entire system and can be regarded as a small disturbance, and the coupling term between slewing and luffing can be ignored. When the wind speed reaches 15 meters per second or even more than 20 meters per second, the change speed of the wind torque is greater than the inertial response speed. At this time, if the comprehensive influence of parameters such as relative wind speed, structural attitude, and inertia distribution is not considered, problems such as overshoot, frequent braking, and inability to stably track the trajectory will occur in the system, ultimately resulting in the over-limit or out-of-control of the load swing. The present invention precisely incorporates the active characteristics of wind-induced disturbances into the modeling framework, forming a closed loop from system identification to drive control, thereby realizing the whole-process management of "absorbing - distributing - coordinating" high-wind disturbances. In addition, the adaptability of this method is not simply driven by neural networks or black-box algorithms, but is an analytical closed-loop self-regulation achieved through real-time parameter modeling.

[0022] Further, in step 1, ultrasonic anemometers are respectively arranged near the tip of the tower crane boom, at the position of the tower cap, and at a predetermined multi-layer height above the tower body base to synchronously collect the incoming flow wind speed, wind direction, and turbulence intensity as the original meteorological data. After generating time stamps for the original meteorological data according to a unified clock, the data is sent to the central processing unit to form a raw wind field data set covering all measurement points within each control cycle.

[0023] To achieve time synchronization, each anemometer unifies the time reference through a time synchronization protocol (such as IEEE 1588 or an internal high-precision clock synchronization module) to ensure that within any control cycle, the data collected at each measurement point has a strictly consistent time stamp, eliminating the potential time sequence deviation problems that may occur during spatial data integration. Through this structured time control, the original meteorological data is integrated into a raw wind field data set according to a unified time reference when sent to the central processing unit. This data set not only contains the wind speed value, wind direction angle, and turbulence index of each sampling point at the current moment but also reflects the spatial gradient distribution of the local wind field through the spatial distribution relationship between the measurement points.

[0024] After receiving this raw wind field data set, the central processing unit further fuses it with the tower crane structure parameters and the current attitude state to construct a "tower crane coupled wind disturbance field model". In this model, the wind speed data of each measurement point is no longer an isolated sample but is mapped to the tower crane reference coordinate system and is associated with the boom attitude in real time to obtain the "position change response of the wind load action direction relative to the tower crane coordinate system". This model is the key innovation point that differentiates this control method from the traditional wind speed threshold speed limit strategy and can capture the spatial dynamic interaction relationship between the tower crane movement and the wind speed change, thereby realizing the dynamic prediction of the subsequent wind-induced coupling moment.

[0025] Specifically, the turbulence intensity, as a key parameter characterizing the frequency characteristics of wind speed disturbance, is not simplified to the mean wind speed deviation in this step but is completely retained as an input variable to participate in the construction of the disturbance term of the subsequent rapid change prediction model of the wind moment, so as to compensate in advance for the rising edge response of the wind-induced interference in the case of high wind load mutations. Finally, this raw wind field data set with complete structure, consistent time, and clear spatial distribution serves as the physical modeling basis, providing data support for the subsequent calculation of the wind-induced coupling moment, disturbance projection, and linkage control, and is input into the main control loop in a structured cache form to ensure that the tower crane control system has the ability to continuously update, quickly respond, and dynamically adapt to high wind load disturbances.

[0026] Furthermore, the central processing unit performs the following processes: implementing multi-level filtering on the original wind field data set, specifically including: using band-pass filtering to suppress low-frequency drift and high-frequency noise, using a sliding time window to smooth gust pulsations, and removing instantaneous distortion samples according to a preset anomaly detection threshold to obtain effective wind speed and effective wind direction with stable statistical characteristics; according to the real-time luffing angle, slewing angle, and boom length of the tower crane, calling a coordinate transformation algorithm to decompose the effective wind speed into a tangential component consistent with the longitudinal direction of the boom and a normal component perpendicular to the boom plane; according to the boom windward projection area database, performing look-up matching on the equivalent windward area in different postures, and combining the tangential component and the normal component with the equivalent windward area to construct a comprehensive wind load field reflecting the instantaneous aerodynamic state of the tower crane; mapping the comprehensive wind load field to the slewing axis coordinate system, and obtaining the instantaneous wind-induced coupling moment acting on the slewing axis by integral method according to the acting arm length from the boom to the slewing center and the boom centroid position; synchronously reading the slewing angular velocity and the tangential linear velocity information of the boom tip of the tower crane, and coupling and correcting the wind-induced coupling moment in combination with the real-time wind direction deviation angle to reflect the real-time influence of the slewing motion on the relative wind speed.

[0027] The real-time wind-induced coupling moment at a certain time is: ; wherein, is the air density; is the resistance coefficient of the boom cross-section; is the windward projection area of the boom; is the measured average wind speed at the sampling height; is the current slewing angular velocity; is the boom length; is the luffing angle; is the slewing angle.

[0028] In a high wind load environment, the structural force characteristics and the essence of the control object of the tower crane have undergone fundamental changes. The wind force is no longer a simple background disturbance, but a dynamically dominant external energy input source. Its scope of action includes not only the suspended load and the boom, but also directly couples into the slewing dynamics and luffing response of the tower crane, thereby changing the state evolution law of the entire system. In order to enable the control system of the tower crane to have the ability to actively resist wind, the first thing to solve is how to accurately quantify the coupling effect of the wind on the structure with a controllable logic and express this quantity and the structure state in a unified manner in the control model. The design of Step 1 is a systematic solution to this problem.

[0029] Its core principle is as follows: The wind field disturbance information is converted into an equivalent dynamic load description quantity in the structural reference system, enabling the wind, as a "driving input", to enter the system dynamics model together with endogenous parameters such as mass, inertia, position, and velocity, thus becoming part of the feedback control. This conversion does not directly control or simply threshold the wind speed. Instead, the wind speed is regarded as a dynamic field variable, and after spatial projection and attitude decoupling, it is mapped into "control influence parameters", such as the coupled wind torque. The prerequisite for this principle to hold is that the tower crane is not a point mass system but a non-linear system with high-order structural distribution and three-dimensional rigid body characteristics. The influence of the wind speed on it cannot be described solely by the "wind speed value" itself but must be converted into forces and torques acting on the structural nodes to participate in the derivation of the system control law. Moreover, such forces and torques not only depend on the wind speed itself but also on the combined effects of the relative direction between the wind speed and the structure, the windward projection area of the structure surface, and the velocity field of the structure during movement.

[0030] Therefore, in step 1, multiple wind measurement points are set. The principle significance is not that "multi-point monitoring is more accurate", but to obtain the gradient distribution information of the local wind field in space to restore the non-uniform action of the wind speed field on each part of the tower crane structure. During the luffing and slewing processes of the tower crane, its attitude is constantly changing, and the relationship between the acting angle of the wind and the structural projection plane is also adjusted in real time. If only a single wind speed value or a simple estimation method is used, the control system will lose the ability to characterize the geometric coupling characteristics of the disturbance source, and the control output will inevitably be delayed or even incorrect. After constructing the wind speed field through multi-point data, the system can "redefine" the wind speed as a relative wind field action function in the structural reference system based on the movement state of the tower crane itself, rather than a single external disturbance. On this basis, the further processing in step 1 - the projection of the wind speed onto the tangential and normal components, the matching and look-up table of the projection area, and the synthesis of the wind load field - is essentially constructing a "wind-induced kinetic energy input model". This model is not used to directly control the wind speed but to estimate the spatially directional disturbing torque exerted by the wind on the tower crane and use it as part of the system state to participate in the generation of the subsequent control law. The emergence of the wind-induced coupling torque is not a human design but the result of introducing field variables in system modeling in structural control. It is an asymmetric disturbance quantity that can dynamically adjust the objectives of the slewing and luffing control strategies without changing the tower crane structure, enabling the control system to transform from a simple "trajectory tracking" logic to a "dynamic regulation under state-disturbance coupling constraints" logic.

[0031] Further, step 2 specifically includes: reading the inherent moment of inertia of the tower body and slewing platform, the self-weight of the boom, the boom length, and the geometric positions of the boom centroid and the slewing center as a set of static design parameters, and locking the set of static design parameters once based on the factory calibration report; obtaining the real-time value of the load mass and the instantaneous position of the load in the longitudinal direction of the boom, combining the luffing angle and slewing angle information shared in step 1, performing coordinate transformation on the vertical projection distance of the load in the slewing plane and the acting arm from the boom to the slewing center, and constructing a dynamic position model of the load mass in the coordinate system of the slewing axis; according to the dynamic equivalent principle of the tower crane, summing up item by item the inherent moment of inertia of the tower body and slewing platform, the self-weight of the boom and its inertia component generated by the change of the luffing angle, and the inertia contribution of the load mass to the slewing axis at the real-time position, and introducing the coupling inertia cross-term between the boom and the load centroid relative to the slewing center during the summing process to obtain the real-time equivalent moment of inertia.

[0032] Real-time equivalent moment of inertia is: ; wherein, is the inherent moment of inertia of the tower body and slewing platform; is the self-weight of the boom; is the mass of the lifting load; is the distance from the slewing center to the vertical projection of the load.

[0033] In specific implementation, this process first takes reading the inherent moment of inertia of the tower body and slewing platform, the self-weight of the boom, the boom length, and the geometric positions of the boom centroid and the slewing center as the starting input, which belong to a set of static design parameters of the tower crane structure. These parameters have been obtained through finite element analysis, center of gravity calibration, and overall machine counterweight test during the tower crane manufacturing stage, and are solidified in the form of a factory calibration report after installation and commissioning. The central processing unit will read and lock these parameters once during the system initialization stage and will not change them during subsequent operation to ensure the consistency and traceability of the system control model. These static design parameters not only provide a reference inertia term for subsequent calculations but also constitute an immutable input part directly related to the structural configuration in the inertia model.

[0034] To introduce dynamics, the system also needs to introduce real-time variables related to the operating state. First, a force measuring device installed on the hook or the tension path of the hoisting wire rope is used to obtain the real-time value of the load mass. At the same time, since the position of the load in the boom direction is not fixed and its influence on the center of rotation is different at different hoisting heights, the system synchronously obtains the instantaneous position of the load in the longitudinal direction of the boom, which is usually indirectly calculated from the position of the luffing trolley or the change in the length of the hoisting rope. Based on the obtained load mass and position, the central processing unit calls the luffing angle and slewing angle information shared in step 1, maps the displacement of the load relative to the boom to the spatial coordinate system in the entire tower crane slewing plane, constructs the vertical projection distance of the load in the slewing plane, and further calculates the geometric moment arm of the load relative to the center of rotation through coordinate transformation. This transformation operation converts the actual spatial displacement into a dynamic projection in the reference coordinate system of the slewing axis, and the result is used to evaluate the degree of inertia influence exerted by the load mass on the slewing axis.

[0035] After completing the acquisition of static and dynamic parameters, the central processing unit starts to execute the real-time inertia solution process based on the dynamic equivalent principle of the tower crane. In this process, the system first introduces the inherent moment of inertia of the tower body and the slewing platform as a constant term into the calculation model, and then processes the self-weight part of the boom. Considering that the luffing angle will cause the spatial position of the boom center of gravity relative to the slewing axis to change, the system adjusts the distance from the boom center of gravity to the center of rotation in real time according to the luffing angle state, so as to correct the contribution of the boom self-weight to the moment of inertia. Subsequently, the system independently estimates the inertia influence of the load mass on the slewing axis at the current instantaneous position. This influence is not only related to the load mass and the distance of the lifting point, but also affected by the influence of the boom attitude on the projection length of the moment arm. Therefore, the system needs to consider the three-dimensional angular relationship between the load point and the center of rotation in the calculation.

[0036] After completing the estimation of all independent components, the central processing unit accumulates them item by item to construct a complete basic inertia synthesis expression. However, simply accumulating the individual inertias cannot fully reflect the coupling behavior of the actual system. In the luffing-slewing linkage state, the self-weight of the boom and the load mass will form a linkage inertia effect during the movement, resulting in cross-influence terms in the actual moment of inertia. Therefore, the system introduces the coupling inertia cross-term between the boom center of mass and the load center of mass relative to the center of rotation, and embeds this term as a linkage compensation amount into the inertia model during the construction of the real-time equivalent moment of inertia. This cross-term is derived from the structural kinematic expression and reflects the influence of the two mass bodies on the total angular momentum response in the non-collinear motion state. It is one of the most core non-linear terms in the entire linkage control modeling.

[0037] Furthermore, the real-time value of the suspended load mass is obtained through a suspended load force measuring pin or a wire rope tension sensor, and the instantaneous position of the suspended load is obtained through a luffing trolley travel encoder; the central processing unit uses the pulse feedback signal of the main hoist lifting drive of the tower crane and the low-frequency swing data collected by the tip inertial measurement unit to check the small swing angles of the suspended load mass in the longitudinal and transverse directions, and corrects the instantaneous spatial coordinates of the suspended load center of mass accordingly; during the inertia accumulation process, exponential weighted moving average filtering is performed on the input of the suspended load mass position and the boom luffing angle, and abnormal sampling points beyond three times the median absolute deviation range are removed through chi-square tests to improve the statistical robustness of the inertia estimation.

[0038] Furthermore, at the end of each control cycle, the central processing unit performs a least squares self-calibration operation by comparing the measured angular acceleration output by the slewing angular velocity sensor with the theoretical angular acceleration predicted based on the real-time inertia model, and makes a slight adjustment to the residuals of the boom center of mass position and the suspended load center of mass position in the coordinate transformation matrix; when the change amplitude of the real-time equivalent moment of inertia relative to the value of the previous cycle exceeds the safety threshold, the inertia freezing logic is triggered and an inertia anomaly alarm is sent to the main controller of the tower crane.

[0039] In the luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments, the central processing unit not only undertakes the task of calculating the equivalent moment of inertia in real time, but also must ensure the credibility, convergence, and physical consistency of this inertia parameter in a dynamic environment. Since the calculation process of the equivalent moment of inertia highly depends on the position calculation of the boom center of mass and the suspended load center of mass in space, and these positions will have time-varying deviations due to factors such as sensor errors, mechanical clearances, and wind-induced deformations, relying solely on forward calculation will cause the inertia model to gradually deviate from the true physical value after multiple cycles of operation. To achieve the continuous physical consistency of the inertia parameter during the control process, the central processing unit designs a least squares self-calibration mechanism driven by sensor feedback.

[0040] The core principle of this self-calibration mechanism is to compare the angular acceleration measured by the gyroscopic angular velocity sensor, which is the actual physical response, with the theoretical angular acceleration derived jointly from the real-time equivalent moment of inertia model constructed based on the current cycle and the known resultant torque. The theoretical angular acceleration is obtained by combining the system dynamics model with real-time inputs and represents the response expectation of the system under ideal modeling assumptions. The angular acceleration provided by the sensor is the feedback output of the tower crane after being affected by wind load, inertia, and structural deviation in the real environment. When there is a systematic deviation between the two, it can be inferred that there are error sources in the modeling process, especially the static offset or dynamic drift of the positions of the boom centroid and the load centroid during the coordinate transformation process. At this time, the system invokes the least squares self-calibration algorithm, with the error between the measured and predicted angular accelerations as the objective function, to minimize the sum of the squares of the residuals over several consecutive control cycles, thereby inversely adjusting the relative position offset parameters of the boom centroid and the load centroid in the coordinate transformation matrix to achieve a minor correction of the inertia estimation model.

[0041] This correction process does not aim to rebuild the model but to online optimize the geometric parameters in the existing model in a fine-tuning manner to achieve dynamic compensation within the allowable control frequency range, enabling the system inertia model to have the performance of "finite convergence and gradual correction". The corrected result is written back to the system status register at the end of the control cycle and used as the initial parameter input for the inertia calculation in the next cycle to achieve the model convergence of cyclic iteration.

[0042] To ensure system stability and avoid model oscillation, the central processing unit also sets up an inertia change monitoring mechanism to continuously compare the change amplitude between the equivalent moment of inertia calculated in the current cycle and the inertia value in the previous cycle. When the change amplitude exceeds the safety threshold jointly defined by the manufacturing tolerance of the tower crane structure and the physical limit of load variation, the system determines that the current inertia model may have significant uncertainties or be affected by non-physical interference. At this time, the inertia freezing logic is immediately triggered to forcibly hold the inertia value of the current cycle as the stable value of the previous cycle, prohibit further updates, and record this state as an inertia anomaly event. An inertia anomaly alarm is synchronously sent to the main controller of the tower crane to prompt the operation and maintenance system or the driver that there may be sensor failures, severe wind load disturbances, out-of-control load swings, or other unexpected structural responses in the current state, thereby preventing overshoot or undershoot of control commands caused by unreliable inertia data.

[0043] During the inertia freezing state, the central processing unit still retains the least squares error monitoring function, but does not immediately update the model parameters. Instead, it enters the observation mode, continuously records the residual sequence between the measured angular acceleration and the prediction of the frozen model, and automatically unfreezes the state and resumes the self-calibration function and the inertia update process after the residuals converge back to the safe error band range for multiple consecutive cycles, ensuring that the control system has the ability of online self-recovery and dynamic adaptation while ensuring safety. This mechanism ensures the physical validity of the core control parameters, prevents the inertia model from having non-substantive drift under multi-source disturbances, and is the key support mechanism for maintaining the model credibility and closed-loop stability in the linkage control structure of the present invention.

[0044] Further, step 3 specifically includes: the central processing unit simultaneously calls the wind-induced coupling torque determined in step 1 and the real-time equivalent moment of inertia determined in step 2 within each control cycle, and calculates the original luffing torque command output by the tower crane luffing motor based on the established tower crane luffing dynamics model to actively compensate for high wind load disturbances; the calculation process includes: forming a closed-loop error signal group containing errors, error change rates, and historical integral quantities based on the target luffing angle trajectory and the real-time measured luffing angle; generating an inertia feedforward component with the real-time equivalent moment of inertia and the desired luffing angular acceleration to offset the uncertainty of the mass distribution change; combining the damping component obtained by filtering the luffing motor speed, the disturbance compensation amount formed by the projection of the suspended load gravity and the wind-induced coupling torque in the luffing plane, and hierarchically synthesizing with the closed-loop error signal group; outputting the original luffing torque command to complete the adaptive control of the luffing mechanism.

[0045] The original luffing torque command is : ; wherein, is the luffing angular acceleration command; is the equivalent viscous damping coefficient of the luffing mechanism; is the luffing angular velocity; is the acceleration due to gravity.

[0046] In the tower crane luffing-slewing linkage adaptive control method for high wind load environments, the adaptive control of the luffing mechanism is a core part of the entire system's linkage logic. Its role lies not only in completing the basic adjustment of the suspended load height and working radius, but more importantly, in actively compensating for the structural response caused by wind-induced disturbances, ensuring that the tower crane jib tip trajectory is consistent with the task planning curve, and suppressing the secondary sway of the suspended load to the greatest extent. To achieve this control goal, the central processing unit dynamically generates the output torque command of the luffing motor based on the tower crane luffing dynamics model, integrating the wind-induced coupling torque from step 1 and the real-time equivalent moment of inertia from step 2 within each control cycle.

[0047] First, the system conducts real-time closed-loop error analysis on the luffing angle trajectory. This analysis process takes the target luffing angle trajectory provided by the upper-layer task planning module as a reference, compares the measured luffing angle displacement in the current cycle, and calculates the instantaneous position error. Based on the first-order difference value of the position error, the error change rate can be obtained. At the same time, the system maintains an integral cumulative value within a time window to form a closed-loop error signal group. This signal group is the core feedback quantity of the controller, reflecting the current attitude deviation degree of the system and its dynamic change trend. Compared with only using the position error for proportional control, this signal group has stronger disturbance response ability and better steady-state tracking performance.

[0048] On the basis of forming the error signal group, the system introduces the product of the real-time equivalent moment of inertia and the desired luffing angular acceleration as a feedforward compensation term. This term reflects the system's predictive response ability to the dynamic load inertia change. Especially when the load mass changes rapidly or the acceleration is significant during the boom telescoping process, it can effectively offset the output hysteresis or error accumulation caused by the change of the structural inertia. This feedforward compensation is based on the real-time equivalent moment of inertia obtained in step 2 of the current cycle, does not rely on fixed model parameters, and has the ability of adaptive adjustment. It is the key mechanism for the system to actively match the structural inertia change.

[0049] Subsequently, the central processing unit introduces a damping component in combination with the operating state of the luffing motor. This component is derived from the current speed signal of the luffing motor and is processed by digital filtering to obtain a smooth speed estimate, which is used to construct a virtual damping torque proportional to the speed. The main function of this damping term is to suppress the residual vibration generated during the rapid movement of the boom. Especially under the action of high wind loads, since the wind speed disturbance spectrum contains high-frequency components and the system has a strong speed response requirement, introducing the damping term can effectively reduce the system oscillation and improve the stability of the controller.

[0050] To further enhance the adaptability of the controller to external disturbances, the system synthesizes the component of the wind-induced coupling torque in the luffing direction from step 1 with the equivalent torque generated by the load gravity on the luffing mechanism at the current attitude to form a disturbance compensation quantity. This disturbance compensation quantity is the real-time response estimation of the system to the two factors of wind load disturbance and gravity disturbance, allowing the controller to perform torque preloading before significant position errors occur, so as to achieve the parallel regulation of "disturbance feedforward + attitude feedback", and enhance the disturbance transparency and response forward-looking of the control system.

[0051] After all the above components are constructed, the central processing unit performs weighted fusion on the feedforward component, damping component, disturbance compensation amount, and closed-loop error signal group according to the preset hierarchical synthesis logic to generate the original luffing torque command. The hierarchical synthesis strategy reflects the system's priority management of different control objectives, that is, emphasizing error integration and damping stability under steady-state control, and emphasizing feedforward accuracy and disturbance rejection ability during dynamic transitions. The finally generated original luffing torque command is the result of multi-source information fusion, with temporal consistency, physical consistency, and disturbance resistance ability, and can be directly sent to the servo drive for luffing motor control execution.

[0052] Through this control process, the system can not only maintain the accuracy of the jib trajectory in a high-wind load environment, but also effectively suppress the dynamic instability problems of the luffing system caused by sudden changes in wind speed, load changes, and structural inertial drift, providing stable and reliable dynamic boundary conditions for the slewing control of the entire tower crane, and constituting an important execution support unit in the luffing-slewing linkage control strategy.

[0053] Furthermore, an integral anti-windup logic is embedded in the stage of generating the original luffing torque command to limit the accumulation speed of the integral amount according to preset conditions to prevent instantaneous torque overshoot caused by strong gusts; when the original luffing torque command is lower than the safety lower limit, the original luffing torque command is set to zero to avoid motor jitter in the low-load area; when the original luffing torque command is higher than the safety upper limit, the peak is clipped according to a linear decreasing curve and a potential overload risk signal is sent; the original luffing torque command after soft limiting processing is cross-checked with operating parameters such as DC bus voltage, braking resistor temperature rise, and servo drive phase margin. If it is found that the braking unit is saturated or the bus voltage exceeds the limit, the energy dissipation priority strategy is triggered, and part of the potential energy feedback sequence is allocated to the slewing or hoisting drive to achieve cross-mechanism energy balance.

[0054] In the luffing-slewing linkage adaptive control method for tower cranes facing high-wind load environments, the generation of the original luffing torque command is not only a calculation process based on error feedback and disturbance compensation, but also a dynamic output regulation process involving multi-level safety mechanisms and energy coordination strategies. Since under high-wind load conditions, wind-induced disturbances often have the characteristics of suddenness and high amplitude. If the control commands are not managed with constraints, it is very easy to cause a series of system instability problems such as torque command mutation, drive overload, structural impact, or vibration amplification. Therefore, in the stage of generating the original luffing torque command, the central processing unit embeds an integrated integral anti-windup logic and operating state-related limiting mechanism to ensure the physical executability of the control output and the electrical safety of the system operation.

[0055] First, the integral anti-windup logic is embedded in the processing path of the closed-loop error signal group. Its control idea is based on setting the integral speed regulation condition to dynamically limit the accumulation rate of the error integral. When it is detected that the amplitude change error is in a continuously rising state, or the error change rate shows exponential growth, and the system is currently in a high wind speed disturbance period, the system will automatically reduce the response speed of the integrator or directly freeze the integral path when necessary, thereby avoiding the sudden soaring of the control torque caused by the error integral. This mechanism effectively curbs the amplification effect of strong gusts or local turbulence on the control output and prevents the system instability problem caused by integral overshoot in the torque response.

[0056] Subsequently, for the numerical range of the original amplitude change torque command, the central processing unit sets a dual soft limiter mechanism and judges and executes it according to the actual operating conditions. If the calculated original amplitude change torque command is lower than the preset safety lower limit, the system directly sets this command to zero, thereby avoiding the periodic jitter or oscillation phenomenon when the motor operates continuously in the extremely low load area and ensuring the stability of the servo execution unit. On the contrary, if the original amplitude change torque command is higher than the safety upper limit, the system does not directly perform clipping, but gradually reduces the peak according to a linear decreasing curve, so that the control output shows a predictable and continuous downward process when approaching the execution limit, reducing the transient impact of the torque boundary effect on the actuator. At the same time, when performing high-limit peak clipping, the central processing unit also generates and sends a potential overload risk signal to the system monitoring module to record the current control state and the possible safety threshold events triggered, providing a basis for subsequent data auditing and abnormal condition reproduction on the operation and maintenance side.

[0057] After the above soft limiter processing, the central processing unit cross-checks the original amplitude change torque command to be issued in the current cycle with the key boundary parameters of the system operation. These operating parameters include but are not limited to the DC bus voltage, the temperature rise level of the braking resistor, and the phase margin of the servo drive. The purpose of the cross-check is to evaluate the execution feasibility of the current control command and whether the electrical system has sufficient energy buffering capacity. In actual operation, if the bus voltage approaches the equipment limit, the resistor temperature continues to rise, or the phase margin is close to the system critical point, it means that the current electrical system is in a high-load operating state, and continuing to maintain or increase the torque command may cause system overload or even failure.

[0058] To this end, when the system detects that the operating parameters exceed the limit or are close to the critical state during cross-checking, it will trigger the energy dissipation priority strategy. The core idea of this strategy is to guide part of the mechanical energy that cannot be fully dissipated due to the accumulation of braking torque in the luffing mechanism to the slewing or hoisting drive unit through cross-mechanism coordinated scheduling, so as to share the energy pressure and maintain the overall energy consumption balance of the system. The implementation of this strategy depends on the energy feedback scheduling module inside the system. This module judges the energy flow path according to the current load conditions and operating capabilities of each actuator, and issues the adjustable energy value and the target distribution mechanism in a non-intrusive manner. In this way, the system not only avoids the torque limitation caused by the energy saturation of a single mechanism, but also realizes the collaborative control and energy self-balance across execution units under severe disturbances of high wind loads.

[0059] Furthermore, in step 4, the central processing unit uses the wind-induced coupling torque obtained in step 1, the real-time equivalent moment of inertia determined in step 2, and the original luffing torque command output in step 3 as input boundary conditions, and performs the following operations according to the tower crane slewing dynamics and the principle of energy conservation to achieve the slewing stability control under high wind load conditions: schedule the projection data of the wind-induced coupling torque in the slewing direction, and perform vector-level synthesis with the overturning component converted from the load gravity in the same period to obtain the instantaneous synthesis torque describing the real-time external disturbance state; call the real-time equivalent moment of inertia, convert the instantaneous synthesis torque into the target angular acceleration, and combine the actual angular velocity and angular acceleration fed back by the slewing driver to form a closed-loop error signal set including speed deviation, acceleration deviation, and historical speed integral; according to the energy shaping idea, calculate the coupling kinetic energy term between the luffing angular velocity and the slewing angular velocity, map it to the angular velocity adjustment amount and superimpose it on the speed deviation to form a preliminary corrected angular velocity setting value, so as to update the slewing angular velocity setting value of the tower crane in the next control cycle in real time, and complete the linkage adaptive control of the tower crane luffing-slewing.

[0060] The slewing angular velocity setting value of the next control cycle is: ; In the tower crane variable amplitude-rotation linkage adaptive control method for high wind load environment, the angular velocity control of the rotation system is not only related to the operation accuracy and motion smoothness, but also the key link of structural safety and load sway control. Under high wind load conditions, due to the non-steady nature, spatial non-uniformity and attitude dependence of wind-induced disturbances, the angular velocity setting based solely on the traditional static model can no longer meet the dynamic control requirements under wind field coupling. Therefore, step 4 introduces an angular velocity adaptive correction mechanism driven by multi-source boundary conditions and with coupled kinetic energy compensation capabilities. The central processing unit uses wind-induced disturbances, structural inertia state and variable amplitude drive output as input variables, and constructs a rotation angular velocity setting value generation path that adapts to wind field changes based on tower crane rotation dynamics and energy conservation principles.

[0061] The process first dispatches the component in the rotation direction from the wind-induced coupling torque obtained in step 1, which is the main source of the disturbance torque directly generated by the wind load on the rotary system. This torque component reflects the relationship between the windward direction and the structural projection under the current posture of the tower crane, and is the main driving item of the external disturbance in the structural motion control. At the same time, the system synchronously reads the mass information of the load in the current cycle, and combines the boom amplitude angle and the vertical projection distance of the load in the rotary plane to calculate the overturning moment component generated by the load gravity on the rotary system. The wind-induced disturbance torque and overturning moment are not linearly superimposed in physical space, but are synthesized in a vector manner in the control model. The resulting instantaneous synthetic torque truly reflects the force distribution of the rotary system under the current structure and load state, and is the core external input variable used to derive the angular velocity response in this control cycle.

[0062] After obtaining the synthetic torque, the central processing unit calls the real-time equivalent moment of inertia provided in step 2, and maps the disturbance torque to the target angular acceleration based on the dynamic relationship of the tower crane's rotary motion. The angular acceleration represents the response trend that the rotary system should have under the current disturbance state. After that, the system retrieves the actual angular velocity and angular acceleration measurement values fed back by the rotary servo drive in the current cycle, and constructs a closed-loop error signal set containing velocity deviation, acceleration deviation and historical velocity integral. This error signal set is the core basis for the controller to adjust the angular velocity. It has dynamic response capability and cumulative error correction capability, and can fully reflect the difference between the current control output of the system and the actual state.

[0063] While forming the error signal set, the central processing unit calculates the kinetic energy coupling relationship between the luffing motion and the slewing motion according to the energy shaping idea of the system. This kinetic energy coupling term comes from the redistribution effect of the luffing acceleration caused by the luffing torque command in step 3 on the kinetic energy distribution of the whole machine system. Since the luffing and slewing mechanisms have spatial cross-action, there is an inner product term for their instantaneous velocity vectors in the inertial reference frame, resulting in non-independent terms in the kinetic energy expression. Therefore, the change in the luffing angular velocity under high wind loads will have an indirect impact on the slewing system, manifested as additional kinetic energy input or output. The system calculates this coupled kinetic energy term through the change rate between the luffing angular velocity and the slewing angular velocity in the current cycle, and converts it into an equivalent angular velocity adjustment amount, which is used as an additional compensation term for correcting the slewing angular velocity setting value.

[0064] This kinetic energy compensation term is superimposed together with the velocity deviation in the aforementioned closed-loop error signal set to form a preliminarily corrected angular velocity setting value. This setting value is no longer a target quantity derived only based on the angle error or disturbing torque, but a dynamic control output after integrating multi-dimensional factors such as the structural state, disturbance dynamics, linkage feedback, and energy coupling, with strong environmental adaptability and response foresight. This corrected angular velocity setting value is written into the target value register of the next control cycle at the end of the cycle, used to drive the slewing servo system for updated control, and serves as a reference benchmark for the execution of subsequent control logic.

[0065] Furthermore, the central processing unit is also equipped with an extreme wind load safety decontrol mechanism, which specifically includes: when the transient impact value monitored by the slewing acceleration sensor exceeds the structural limit threshold, it immediately enters the three-level decontrol mode. In the first stage, the slewing servo angular velocity command is frozen and a cooperative deceleration request is broadcast to the luffing drive module; in the second stage, the impact of the wind-induced steep rise on the slewing system is reduced by dynamically adjusting the hook horizontal damping and the opening of the tower top wind blocking plate; in the third stage, after confirming that the wind speed and the swing amplitude of the load have dropped back to the controllable range, the freezing is gradually released and the closed-loop adaptive correction process is restored; during the decontrol period, the remaining wind-induced coupling torque in the slewing direction is continuously calculated in a low-frequency scanning manner, and normal control is automatically re-enabled when the safety window appears.

[0066] In the tower crane luffing-slewing linkage adaptive control method for high wind load environments, the central processing unit, in addition to the high-frequency closed-loop control function, must also be equipped with an extreme working condition response mechanism with structural safety assurance capabilities to cope with impact load events caused by sudden wind loads. In the actual operation of the tower crane, wind field fluctuations often contain components such as low-frequency shear layers, gust pulsations, and turbulent peaks. Especially under high wind speed boundary conditions, wind-induced loads may rise sharply in a very short time, causing transient shocks to the slewing system that far exceed the inertial response capability. If such shocks exceed the structural design limit and the conventional control logic is still maintained, it may cause irreversible consequences such as load swing amplification, servo instability, and even structural damage. To this end, the central processing unit sets a three-level progressive extreme wind load safety retreat control mechanism to ensure that the system can automatically interrupt the conventional control path when signs of potential structural overload are detected, and implement control degradation and coordinated load reduction strategies in accordance with the principle of safety priority.

[0067] The start-up conditions of the decontrol mechanism are based on the measured data of the slewing acceleration sensor. The central processing unit continuously monitors the angular acceleration response curve of the slewing system in each control cycle, and compares its measured peak value with the predefined limit threshold in the structural database. When the absolute value or rate of change of the angular acceleration exceeds the structural limit threshold, the system immediately enters the first stage of decontrol mode. The action of the first stage is to freeze the slewing servo angular velocity instruction, that is, immediately terminate the update of the slewing velocity target generated in the current cycle, and keep the output state of the servo drive at the current value or the safe stagnation state to prevent the system from continuing to advance the attitude correction process during the impact. At the same time, the central processing unit sends a broadcast-style coordinated deceleration request to the amplitude variable drive module, instructing it to reduce the amplitude variable angular velocity or actively retract the boom length, reduce the wind load projection area of the overall system, and thus reduce the total structural force in a linkage manner.

[0068] After entering the second stage, the system is no longer limited to the control level, but links the actuators and mechanism auxiliary devices to carry out wind load reduction operations. First, dynamically adjust the response parameters of the hook horizontal damping module, such as increasing the damper oil circuit throttling ratio or enabling the bypass flow limiting channel to enhance the energy consumption capacity of the load sway; secondly, adjust the opening of the tower top wind baffle according to the direction and amplitude state of the wind field, and guide the wind flow deflection or pressure relief in the local area by aerodynamic means to reduce the accumulation of wind pressure peaks on the surface of the structure, thereby reducing the rate of increase of wind-induced coupling torque. This stage focuses on delaying the shock transmission rate by means of flexible buffering at the structural level when the external disturbance has not been completely released, providing a transition zone for subsequent control recovery.

[0069] After the above two stages of response and relief, the system enters the third stage, which is to determine whether the conditions for restoring normal control are met. The central processing unit continuously reads the data stream of the wind speed monitoring device and the load swing amplitude estimation module. When the wind speed falls back to the designed safety envelope range and the load swing amplitude is within the controllable range, the system gradually releases the freezing logic, re-enables the real-time update function of the rotation angular velocity setting value, and resumes the adaptive correction process. This release process is not an instantaneous recovery, but a transition to the target angular velocity setting state through smooth interpolation within multiple cycles, ensuring that the system has continuity and response stability when re-entering the closed-loop control path, avoiding the "recovery jump" phenomenon.

[0070] During the entire decontrol cycle, although the angular velocity command is frozen, the central processing unit still maintains the low-frequency scanning mechanism, periodically calculates the residual component of the current wind-induced coupling torque in the rotation direction, and judges the stability of wind farm recovery based on its change trend. When the residual wind-induced torque drops significantly or tends to be stable, and the fluctuation amplitude is within the preset range, it is considered that the current environment has a "safety window" for re-entering conventional control. The system automatically determines and enters the control process reset state, and restores all control logic such as wind-induced torque compensation, inertia dynamic update, and rotation speed closed-loop regulation.

[0071] The following is an example of a specific implementation scheme based on the "tower crane luffing-slewing linkage adaptive control method for high wind load environment" of the present invention. Assume that a tower crane at a construction site is operating in a sea breeze environment, with a height of 80 meters, a boom length of 60 meters, a current luffing angle of 40 degrees, a slewing angle of 120 degrees, a hoisting mass of 3.2 tons, and a real-time average wind speed of 18 meters per second. The tower crane is equipped with ultrasonic wind measuring devices at three height points, which are respectively arranged at the tower base (0 meters), the tower cap (80 meters) and near the tip of the boom (about 78 meters high). First, the central processing unit receives the wind speed data of the three wind measuring devices in the current control cycle, and after timestamp alignment and unified clock synchronization, performs bandpass filtering (setting the lower limit of the filter to 0.1 Hz and the upper limit to 10 Hz) to remove low-frequency drift and high-frequency electrical noise, and obtains effective wind speed data of 16.5, 18.2, and 18.0 meters per second, respectively. The sliding time window width is set to 300 milliseconds to smooth the gust components; after eliminating data jump samples based on the preset standard deviation threshold, the current effective average wind speed is calculated to be 17.6 meters per second, and the wind direction is 5 degrees north and east.

[0072] According to the current posture of the boom and the coordinate transformation algorithm, the effective wind speed is decomposed into a tangential component consistent with the longitudinal direction of the boom, which is 12.3 m / s, and a normal component perpendicular to the boom plane, which is 9.8 m / s. At this time, the central processing unit looks up the table in the posture-area database and obtains the windward projection area corresponding to a luffing angle of 40 degrees, which is 38.6 square meters. Through the aerodynamic model, the total wind load acting on the boom by the comprehensive wind load field is calculated to be 2,200 Newtons. Taking the horizontal projection distance from the boom's center of gravity to the slewing center as 30.2 m as the acting arm, the wind-induced coupling moment can be obtained by multiplication as 66,440 N·m. Considering the load factor again, the load mass is 3.2 tons, and its longitudinal distance is 80% of the effective length of the boom, that is, 48 m. Combining the current slewing angle and luffing angle, the vertical projection distance of the load's center of mass in the coordinate system of the slewing axis is converted to 42.5 m, and the contribution of its dynamic inertia to the slewing axis is synthesized to be approximately 5,780 kg·m². The static moment of inertia of the tower and slewing platform is 3,850 kg·m², and the self-weight of the boom is 4.8 tons. The change in inertia caused by the luffing angle is calculated to be approximately 1,630 kg·m². Thus, the real-time equivalent moment of inertia in the current cycle is 3,850 + 1,630 + 5,780 = 11,260 kg·m².

[0073] On this basis, according to the requirements of the upper-level task, the central processing unit needs to adjust the luffing angle from the current 40 degrees to 42 degrees in the next cycle, and the target luffing angular acceleration is planned to be 0.15 rad / s². Multiply this acceleration by the equivalent moment of inertia to obtain the inertia feedforward component of 1,689 N·m. At this time, the measured speed of the luffing motor is 0.18 rad / s, and the damping component obtained after low-pass filtering is 56 N·m; according to the load position and mass, the disturbing torque contributed by the gravity component in the luffing direction under the current posture is 1,524 N·m, and the projection of the wind-induced coupling moment in the luffing direction is 448 N·m. The combined disturbance compensation amount is 1,972 N·m. The error correction amount is obtained by synthesizing the error term, change rate, and integral value of the closed-loop error signal group corresponding to the feedback term, which is 432 N·m.

[0074] After synthesizing all the above components, the original luffing torque command is 1,689 + 56 + 1,972 + 432 = 4,149 N·m. Considering that the safety upper limit set by the current system is 4,000 N·m, the central processing unit triggers a linear peak clipping mechanism, smoothly reduces the excess part to the target limit value, and reports a potential overload risk event to the system monitoring module. After soft limiting processing, the finally output luffing torque command is 4,000 N·m.

[0075] Then it enters the rotation control process. The central processing unit dispatches the wind-induced coupling torque projection in the rotation direction to 61,000 Nm, the load gravity overturning component to 28,700 Nm, and the resultant torque to 89,700 Nm. Dividing this value by the real-time inertia of 11,260 kg m², the target angular acceleration is 7.96 radians per square second. The current angular acceleration of the rotation servo feedback is 6.72 radians per square second, and the speed deviation is 0.34 radians per second. Combined with the historical integral speed of 0.23 radians per second, a closed-loop error signal group is formed. Since the current amplitude angular velocity is 0.12 radians per second, the system calculates the amplitude-rotation coupling kinetic energy term to be 0.89 Nm, and the corresponding speed compensation is 0.08 radians per second. The final angular velocity correction value is the original angular velocity target plus the comprehensive adjustment after the error response and kinetic energy compensation, and the generated target angular velocity setting value is 1.12 radians per second.

[0076] When the angular velocity setting value is written into the slewing servo command in the next cycle, due to the short-term peak wind speed rising to 24 meters per second, the central processing unit detects that the angular acceleration reaches the critical threshold of 9.7 radians per square second, exceeding the structural safety limit of 8.5 radians per square second, and immediately triggers the extreme wind load safety decontrol mechanism. The current slewing angular velocity setting value is frozen, and the amplitude adjustment system executes deceleration to 0.05 radians per second. At the same time, the hook damping valve is instructed to increase the damping ratio, and the opening of the tower top wind damper is adjusted from 60% to 90%. When the wind speed drops back to 15 meters per second and the load sway angle is less than 1.5 degrees, the system gradually releases the decontrol and resumes the closed-loop control process.

[0077] Figure 2 This is the result of the linkage control performance test. As shown in the figure, in the luffing angle response part, the horizontal axis represents time (unit: seconds), the time range is 0-10 seconds, and the vertical axis represents the luffing angle (unit: degree), the angle range is 0-40 degrees. The target value setting line is represented by a dotted line, showing a linear upward trend from the lower left to the upper right, with a starting point of about 15 degrees and an end point of about 35 degrees. The slope remains constant, indicating that the system preset luffing angle gradually increases with time at a fixed rate, reflecting the uniform motion control strategy of the luffing mechanism. The actual value response curve is represented by a solid line, showing that in the initial stage (0-2 seconds), the actual angle value is significantly lower than the target setting value, and there is a large tracking error of about 8-10 degrees. This phenomenon is mainly due to the inertial characteristics of the tower crane luffing mechanism and the dynamic response delay during the system startup process. As time goes by (2-6 seconds), the slope of the actual value curve gradually increases, indicating that the control system continuously adjusts the control parameters through the adaptive algorithm to accelerate the angle tracking speed. After about 6 seconds, the actual value curve basically coincided with the target value curve, and the tracking error was reduced to less than 2 degrees, demonstrating excellent angle control performance and system stability.

[0078] In the response part of the rotational angular velocity, the abscissa also represents time (unit: second), and the time range is from 0 to 10 seconds. The ordinate represents the rotational angular velocity (unit: degree / second), and the angular velocity range is from 0 to 4 degrees / second. The area affected by wind load disturbance is specifically marked in the figure. This area is within the time range of 4 - 6 seconds on the time axis, highlighted by a dashed rectangular box, and clearly marked with the words "wind load disturbance" and "affected area", indicating that the system is significantly disturbed by external wind loads during this time period. Within this affected area, the target value is set as a horizontal constant line of 2 degrees / second, indicating that the desired rotational angular velocity should remain stable. The actual value response curve remains relatively stable outside the wind load disturbance area (0 - 4 seconds and 6 - 10 seconds), and the angular velocity value is stable near 2 degrees / second, with a fluctuation amplitude less than 0.2 degrees / second. However, within the wind load disturbance affected area (4 - 6 seconds), obvious fluctuations occur in the actual value curve. First, it rapidly rises from 2 degrees / second to approximately 3.2 degrees / second, then drops sharply to approximately 1.5 degrees / second, and finally readjusts back to near 2 degrees / second at the end of the area. The peak deviation of this response characteristic reaches 1.2 degrees / second, fully reflecting the significant impact of wind load disturbance on the rotational motion, and at the same time verifying that the proposed adaptive control algorithm of the present invention can effectively suppress the disturbance impact within about 2 seconds. By adjusting the control parameters and the linkage compensation mechanism in real time, the stable tracking of the target angular velocity is ultimately achieved. Figure 3It is a comparison chart of the luffing moment control effect. Through the form of the time-moment curve, this chart intuitively shows the significant differences in the luffing moment control performance between the traditional control method and the luffing-slewing linkage adaptive control method for tower cranes facing high-wind load environments described in the present invention. In the figure, the abscissa represents the time axis with the unit of seconds, and the ordinate represents the magnitude of the luffing moment. The dashed curve represents the change of the luffing moment when the traditional control method is adopted, and the solid curve represents the change of the luffing moment when the control method of the present invention is adopted. In the high-wind load disturbance interval, the moment curve of the traditional control method shows obvious fluctuation characteristics, and the difference between the moment peak value and the valley value is large, indicating that it is difficult for the traditional method to maintain a stable moment output in the face of wind load disturbances, and it is easy to generate large control deviations and system oscillations. In contrast, under the same high-wind load disturbance conditions, the luffing moment curve of the control method of the present invention remains relatively stable, and the moment fluctuation amplitude is significantly reduced. This improvement effect is mainly attributed to the real-time calculation and compensation mechanism of the wind-induced coupling moment and the dynamic adjustment function of the real-time equivalent moment of inertia in the present invention. Through the wind-induced coupling moment obtained in step 1 and the real-time equivalent moment of inertia determined in step 2, the system can actively compensate for the wind load disturbance in each control cycle, thereby effectively suppressing the moment fluctuation. The test data shows that by adopting the control method of the present invention, the luffing moment fluctuation is reduced by 65%, the control accuracy is improved by 40%, and the response time is shortened by 30%. The improvement of these performance indicators directly reflects the control advantages of the present invention in high-wind load environments, providing a strong guarantee for the safe and stable operation of tower cranes under adverse weather conditions.

[0079] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. The luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments is characterized in that The method includes the following: Step 1: Obtain the measured average wind speed at the height where the tower crane is located. Combine the slewing angular velocity, boom length, luffing angle, and slewing angle of the tower crane to calculate the windward projected area and relative wind speed of the boom, so as to determine the wind-induced coupling moment acting on the slewing axis of the tower crane. Step 2: According to the inherent moment of inertia of the tower crane, the self-weight of the boom, the load mass, the boom length, the luffing angle, and the slewing angle, calculate the vertical projection distance from the slewing center of the tower crane to the load, and calculate the real-time equivalent moment of inertia generated by the self-weight of the boom, the load mass, and their relative positions in real time. Step 3: Obtain the original luffing moment command for the output of the luffing motor of the tower crane through the sum of the product of the real-time equivalent moment of inertia and the luffing angular acceleration command, the viscous damping effect of the luffing mechanism, the gravity moment generated by the load mass, and the projection of the wind-induced coupling moment in the luffing direction. Step 4: Use the coupled moment of inertia of the slewing axis to convert the projection of the calculated wind-induced coupling moment in the slewing direction, the overturning component of the gravity of the load mass on the slewing axis, and the kinetic energy coupling effect caused by the linkage of the luffing angular velocity and the slewing angular velocity into the correction amount of the slewing angular velocity, so as to update the slewing angular velocity setting value of the tower crane in the next control cycle in real time, and complete the coupled adaptive control of the luffing-slewing of the tower crane.

2. The luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments according to claim 1, characterized in that, In Step 1, ultrasonic anemometers are respectively arranged near the tip of the tower crane boom, at the position of the tower cap, and at a predetermined multi-layer height above the tower body base to synchronously collect the incoming flow wind speed, wind direction, and turbulence pulsation intensity as the original meteorological data; the original meteorological data is sent to the central processing unit after generating time stamps according to a unified clock to form a wind field original data set covering all measurement points in each control cycle.

3. The luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments according to claim 2, wherein, The central processing unit performs the following process: perform multi-level filtering processing on the wind field original data set, specifically including: using band-pass filtering to suppress low-frequency drift and high-frequency noise, using a sliding time window to smooth gust pulsations, and removing instantaneous distortion samples according to a preset abnormal detection threshold to obtain the effective wind speed and effective wind direction with stable statistical characteristics; according to the real-time luffing angle, slewing angle, and boom length of the tower crane, call the coordinate transformation algorithm to decompose the effective wind speed into a tangential component consistent with the longitudinal direction of the boom and a normal component perpendicular to the boom plane; according to the boom windward projected area database, perform look-up table matching on the equivalent windward area in different postures, and combine the tangential component and the normal component with the equivalent windward area to construct a comprehensive wind load field reflecting the instantaneous aerodynamic state of the tower crane; map the comprehensive wind load field to the slewing axis coordinate system, and calculate the wind-induced coupling moment acting on the slewing axis instantaneously through the integral method according to the acting arm length from the boom to the slewing center and the boom centroid position; synchronously read the slewing angular velocity and the tangential linear velocity information of the boom tip of the tower crane, and perform coupling correction on the wind-induced coupling moment in combination with the real-time wind direction deviation angle to reflect the real-time influence of the slewing motion on the relative wind speed.

4. The luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments according to claim 3, wherein Step 2 specifically includes: reading the inherent moment of inertia of the tower body and the slewing platform, the deadweight of the boom, the length of the boom, and the geometric position of the center of mass of the boom and the center of rotation as a set of static design parameters, and locking the static design parameter set once based on the factory calibration report; obtaining the real-time value of the load mass and the instantaneous position of the load in the longitudinal direction of the boom, combining the amplitude angle and rotation angle information shared in step 1, transforming the vertical projection distance of the load in the rotation plane and the action arm from the boom to the center of rotation, and constructing a dynamic position model of the load mass in the rotation axis coordinate system; according to the tower crane dynamics equivalence principle, the inherent moment of inertia of the tower body and the slewing platform, the deadweight of the boom and its inertia component caused by the change of the amplitude angle, and the inertia contribution of the load mass to the rotation axis at the real-time position are accumulated separately, and the coupling inertia cross term between the boom and the center of mass of the load relative to the rotation center is introduced in the accumulation process to obtain the real-time equivalent moment of inertia.

5. The luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments according to claim 4, characterized in that The real-time value of the load mass is obtained through the load force measuring pin or the wire rope tension sensor, and the instantaneous position of the load is obtained through the stroke encoder of the boom trolley. The central processing unit uses the pulse feedback signal of the tower crane's main hoisting drive and the low-frequency swing data collected by the arm tip inertial measurement unit to verify the tiny swing angles of the load mass in the longitudinal and lateral directions, and use this to correct the instantaneous spatial coordinates of the load's center of mass. In the process of inertia accumulation, exponentially weighted moving average filtering is implemented on the load mass position and boom boom angle inputs, and the abnormal sampling points that exceed the range of three times the median absolute deviation are eliminated through the chi-square test to improve the statistical robustness of inertia estimation.

6. The luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments according to claim 5, characterized in that, At the end of each control cycle, the central processing unit performs a least squares self-calibration operation by comparing the measured angular acceleration output by the rotational angular velocity sensor with the theoretical angular acceleration predicted based on the real-time inertia model, and makes slight adjustments to the residuals of the boom center of mass position and the load center of mass position in the coordinate transformation matrix; when the numerical change of the real-time equivalent moment of inertia relative to the previous cycle exceeds the safety threshold, the inertia freezing logic is triggered and an inertia abnormality alarm is issued to the tower crane main controller.

7. The luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments according to claim 6, wherein, Step 3 specifically includes: the central processing unit simultaneously calls the wind-induced coupling torque determined in step 1 and the real-time equivalent moment of inertia determined in step 2 in each control cycle, and calculates the original amplitude torque command output by the tower crane amplitude motor based on the established tower crane amplitude dynamics model to implement active compensation for high wind load disturbance; the calculation process includes: forming a closed-loop error signal group containing error, error change rate and historical integral according to the target amplitude angle trajectory and the real-time measured amplitude angle; generating an inertia feedforward component with the real-time equivalent moment of inertia and the expected amplitude angle acceleration to offset the uncertainty of mass distribution change; combining the damping component obtained by filtering the amplitude motor speed, the disturbance compensation formed by the projection of the load gravity and the wind-induced coupling torque in the amplitude plane, and hierarchically synthesizing them with the closed-loop error signal group; outputting the original amplitude torque command to complete the adaptive control of the amplitude mechanism.

8. The luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments according to claim 7, wherein Integral anti-saturation logic is embedded in the generation stage of the original variable amplitude torque command, and the integral accumulation speed is limited according to the preset conditions to prevent strong gusts from causing instantaneous torque overshoot. When the original variable amplitude torque command is lower than the safety lower limit, the original variable amplitude torque command is set to zero to avoid motor jitter in the low load area. When the original variable amplitude torque command is higher than the safety upper limit, the peak is clipped according to the linear decreasing curve and a potential overload risk signal is sent. The original variable amplitude torque command processed by soft limiting is cross-checked with operating parameters such as DC bus voltage, brake resistor temperature rise and servo drive phase margin. If the brake unit is found to be saturated or the bus voltage is over-limited, the energy dissipation priority strategy is triggered to allocate part of the potential energy feedback sequence to the slewing or lifting drive to achieve cross-mechanism energy balance.

9. The luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments according to claim 8, characterized in that In step 4, the central processing unit uses the wind-induced coupling torque obtained in step 1, the real-time equivalent moment of inertia determined in step 2, and the original amplitude change torque command output in step 3 as input boundary conditions in each control cycle, and performs the following operations according to the tower crane rotation dynamics and energy conservation principle to achieve rotation stability control under high wind load environment: dispatch the projection data of the wind-induced coupling torque in the rotation direction, and perform vector-level synthesis with the overturning component converted from the load gravity in the same cycle to obtain the instantaneous synthetic torque describing the real-time external disturbance state; call the real-time equivalent The instantaneous synthetic torque is converted into the target angular acceleration according to the moment of inertia, and the actual angular velocity and angular acceleration fed back by the slewing drive are combined to form a closed-loop error signal set including velocity deviation, acceleration deviation and historical velocity integral. According to the energy shaping idea, the coupling kinetic energy term between the amplitude variation angular velocity and the slewing angular velocity is calculated, and it is mapped into an angular velocity adjustment amount and superimposed on the velocity deviation to form a preliminary corrected angular velocity setting value, so as to update the slewing angular velocity setting value of the tower crane in the next control cycle in real time, and complete the linkage adaptive control of the amplitude variation-slewing of the tower crane.

10. The luffing-slewing linkage adaptive control method for tower cranes facing high wind load environments according to claim 9, wherein, The central processing unit is also equipped with an extreme wind load safety back-off control mechanism, which specifically includes: when the transient impact value monitored by the slewing acceleration sensor exceeds the structural limit threshold, it immediately enters the three-level back-off control mode, in which the first stage freezes the slewing servo angular velocity command and broadcasts a coordinated deceleration request to the variable amplitude drive module; the second stage reduces the impact of the wind-induced sudden rise on the slewing system by dynamically adjusting the horizontal damping of the hook and the opening of the tower top wind baffle; in the third stage, after confirming that the wind speed and the swing amplitude of the load have fallen back to a controllable range, the freeze is gradually lifted and the closed-loop adaptive correction process is restored; during the back-off control period, the residual wind-induced coupling torque in the slewing direction is continuously calculated by low-frequency scanning, and normal control is automatically re-enabled when the safety window appears.

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