S curve and closed-loop motion control method and system for stacker

Abstract

The invention relates to the technical field of equipment control, in particular to an S-curve and closed-loop motion control method and system for a stacker, and provides the following scheme: a multi-section speed change curve is generated by acquiring parameters such as a target position, speed, acceleration, jerk and a structural rigidity level; and carrying out resonance risk analysis and curve correction in combination with a frequency spectrum prediction model. A structural modal database and a feedback compensation mechanism are introduced in the control process, feedforward modulation based on modal avoidance and closed-loop control based on error compensation are achieved, the operation stability and positioning precision of the stacking machine are improved, and the method is suitable for stacking machine structures with various rigidity levels.

Description

Technical Field

[0001] The present application relates to the field of equipment control technology, and in particular to an S-curve and closed-loop motion control method and system for a stacker. Background Art

[0002] In existing technologies, stacker crane motion control typically utilizes preset acceleration curves coupled with traditional PID controllers for trajectory tracking. While this approach can achieve basic travel and positioning functions under general operating conditions, it still suffers from significant deficiencies in complex applications. For example, during high-speed travel or long-stroke movements, structural vibration, end-of-line rebound, and positioning overshoot often occur during operation. These issues are particularly prominent in flexible stacker cranes or those with extra-high column structures, impacting equipment stability and response consistency.

[0003] Furthermore, most current control methods generate curves based solely on kinematic constraints, failing to effectively incorporate the rigidity of the stacker crane structure. This can lead to the curves themselves stimulating structural resonance, further exacerbating vibrations and accuracy fluctuations during operation. Furthermore, even with PID closed-loop feedback control for error correction, it is difficult to completely eliminate the impact of structural vibration on end-position accuracy. In particular, when approaching the target point, brief inertial swings and impact oscillations may still occur, making it difficult to meet the requirements of high-precision stacking operations.

[0004] To solve the above problems, the present application designs an S-curve and closed-loop motion control method and system for a stacker. Summary of the Invention

[0005] This application addresses the shortcomings of existing technologies by providing an S-curve and closed-loop motion control method and system for stackers. By acquiring parameters such as target position, velocity, acceleration, jerk, and structural rigidity level, a multi-segment velocity variation curve is generated. This system, combined with a spectrum prediction model, performs resonance risk analysis and curve correction. A structural modal database and feedback compensation mechanism are introduced into the control process to implement modal avoidance-based feedforward modulation and error compensation-based closed-loop control, improving the stacker's operational stability and positioning accuracy. The system is applicable to stacker structures with diverse rigidity levels.

[0006] To achieve the above object, the application provides the following technical scheme: a S-curve and closed-loop motion control method for a stacker, the stacker comprising a controller and a driver, the method comprising: obtaining user setting parameters; generating a speed change curve and a position change curve according to the user setting parameters, wherein the speed change curve is determined according to a preset speed change curve function, and the position change curve is obtained by integrating the speed change curve; discretizing the speed change curve and the position change curve to obtain corresponding theoretical speed values and theoretical position values in each control period. An output rotating speed of the driver is obtained according to the theoretical speed values, and an actual position of the stacker is obtained according to the output rotating speed, the actual position is compared with the theoretical position values, and a compensation speed value is generated according to the comparison result and superimposed on the theoretical speed value of the current control period to update the output rotating speed.

[0007] The speed change curve comprises at least one of four curve types, five curve types, six curve types and seven curve types, wherein the four curve types comprise an acceleration acceleration segment, an acceleration reduction segment, a deceleration increase segment and a deceleration reduction segment, the five curve types comprise an acceleration acceleration segment, an acceleration reduction segment, a speed constant speed segment, a deceleration increase segment and a deceleration reduction segment, the six curve types comprise an acceleration acceleration segment, an acceleration constant segment, an acceleration reduction segment, a deceleration increase segment, a deceleration constant segment and a deceleration reduction segment, and the seven curve types comprise an acceleration acceleration segment, an acceleration constant segment, an acceleration reduction segment, a constant speed segment, a deceleration increase segment, a deceleration constant segment and a deceleration reduction segment.

[0008] The user setting parameters comprise a target position, a target maximum speed, a maximum acceleration and a jerk, and the speed change curve is generated according to the user setting parameters, comprising: judging a corresponding curve type according to the target position, the target maximum speed, the maximum acceleration and the jerk; and calculating the speed change curve through a preset speed change curve function according to the curve type.

[0009] The acceleration time and the deceleration time of the driver are set as the minimum time unit supported by the driver. The actual position is compared with the theoretical position values, and a compensation speed value is generated according to the comparison result and superimposed on the theoretical speed value of the current control period, comprising: generating a compensation amount for correcting a speed instruction through a PID control algorithm according to the deviation between the actual position and the theoretical position values, superimposing the compensation amount on the theoretical speed value corresponding to the current control period to generate an updated speed instruction, and sending the updated speed instruction to the driver, wherein the parameters of the proportional term, the integral term and the differential term in the PID control algorithm are adjusted according to the deviation.

[0010] The user-set parameter further comprises a structural rigidity level of the stacker, the structural rigidity level being determined according to structural dimensions, component materials and historical vibration responses of the stacker, and the speed change curve is calculated according to the curve type, by means of a preset speed change curve function, in combination with a preset frequency spectrum prediction mapping model and the structural rigidity level, wherein the frequency spectrum prediction mapping model is obtained by performing offline modal identification on the stacker, and the offline modal identification comprises extracting inherent modal frequencies, damping ratios and mode shape distributions of the stacker corresponding to the structural rigidity level in a motion state, to generate a frequency spectrum modal database.

[0011] The speed change curve is calculated by means of a preset speed change curve function, in combination with a preset frequency spectrum prediction mapping model and the structural rigidity level, and the calculation comprises: calculating an initial speed change curve according to the curve type, by means of a preset speed change curve function; performing time domain discrete processing on the initial speed change curve to obtain input parameters of the frequency spectrum prediction mapping model; performing Fourier transform on an acceleration change rate of the input parameters by means of the frequency spectrum prediction mapping model, to obtain a frequency spectrum excitation map, and obtaining a structural excitation frequency band according to an energy density distribution of each frequency point in the frequency spectrum excitation map; matching the structural excitation frequency band with structural modal information recorded in the frequency spectrum modal database, to obtain a curve segment with a risk of exciting resonance, wherein the matching is based on a resonance risk judgment rule, and the structural excitation frequency band and the inherent modal frequencies of the structural modal information are evaluated, and the resonance risk judgment rule comprises: when an energy density of a frequency point in the structural excitation frequency band is greater than or equal to a preset modal threshold value, and the corresponding frequency point belongs to a resonance sensitive frequency band range of a modal frequency, it is determined that the corresponding curve segment has a risk of exciting structural resonance; and the curve segment is corrected to obtain the speed change curve.

[0012] The curve segment is modified to obtain a speed change curve, including: parameter reconstruction of the curve segment by a perturbation optimization algorithm, the parameters including an acceleration change rate corresponding to the curve segment, a curve segment duration, and start and end speed values within the curve segment, wherein the perturbation optimization algorithm is configured as a nonlinear search algorithm based on a genetic mechanism, the nonlinear search algorithm including population initialization, fitness evaluation, crossover operation, mutation operation, and termination determination, a fitness function in the fitness evaluation being a frequency spectrum excitation energy integral value corresponding to the structural excitation frequency band, and the termination determination taking the fitness function converging to a preset termination threshold as a determination condition; optimization of the initial speed change curve according to the reconstructed parameters to obtain a plurality of candidate speed change curves, input of the candidate speed change curves into the frequency spectrum prediction mapping model to obtain frequency spectrum excitation maps corresponding to the candidate speed change curves; selection of a candidate speed change curve corresponding to a frequency spectrum excitation map having the maximum Euclidean distance from the natural mode frequency and the minimum total spectrum energy from the candidate speed change curves as a modification result of the initial speed change curve, and generation of the speed change curve.

[0013] The actual position is compared with the theoretical position value, and a compensation speed value is generated according to a comparison result and superimposed on a theoretical speed value of a current control period, and further comprising: obtaining a structural rigidity level of the stacker; according to the structural rigidity level, calling a preset PID control parameter table corresponding to the structural rigidity level to set the coefficient values of the proportional term, the integral term, and the differential term.

[0014] A S-curve and closed-loop motion control system for a stacker, the system comprising: a trajectory generation module for generating a speed change curve and a position change curve according to user-set parameters, and discretely processing the speed change curve and the position change curve to obtain theoretical speed values and theoretical position values corresponding to each control period; a spectrum analysis module for, after generating an initial speed change curve, performing frequency domain conversion on the initial speed change curve based on a frequency spectrum prediction mapping model, identifying curve segments that have a risk of exciting structural resonance, and performing resonance matching and judgment in combination with frequency spectrum modal database information; a trajectory optimization module for performing parameter reconstruction of the curve segments that have the risk of resonance based on a perturbation optimization algorithm, generating a plurality of candidate speed change curves, and screening the candidate speed change curves to obtain a speed change curve; and an adaptive control module for performing closed-loop PID control according to a feedback position deviation from the theoretical speed value, generating a speed compensation amount in real time and superimposing the speed compensation amount on the theoretical speed value, and outputting an updated speed instruction to a stacker driver.

[0015] Compared with the prior art, the beneficial effects of the present application are: the present application realizes adaptive generation of motion trajectory curve for different structural characteristics of the stacker by introducing structural rigidity level, spectrum prediction mapping model and resonance avoidance optimization mechanism, and avoids the structural resonance phenomenon caused by unreasonable trajectory parameter setting. Combined with the frequency band excitation evaluation and optimization correction algorithm based on modal identification, the curve effectively avoids structural modal frequency excitation while ensuring time efficiency, improves the stability and positioning consistency of the motion process. BRIEF DESCRIPTION OF DRAWINGS

[0016] Other features, objects and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments with reference to the attached drawings.

[0017] Figure 1 An exemplary application scenario of an embodiment of the present application.

[0018] Figure 2 A module diagram of the controller of an embodiment of the present application.

[0019] Figure 3 A flow diagram of a S-curve and closed-loop motion control method for a stacker according to an embodiment of the present application.

[0020] Figure 4 A seven-segment curve trajectory diagram according to an embodiment of the present application.

[0021] Figure 5 A flow diagram of a speed change curve generation method according to an embodiment of the present application.

[0022] Figure 6 A flow diagram of another speed change curve generation method according to an embodiment of the present application.

[0023] Reference signs: 100, ground rail; 101, overhead rail; 102, base; 103, driver; 104, column; 105, controller; 1051, curve generation module; 1052, vibration identification module; 1053, adaptive feedback control module. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments.

[0025] Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. As will be apparent to those of ordinary skill in the art, embodiments described herein can be combined with other embodiments.

[0026] The present application is suitable for a stacker system with long-stroke, low-rigidity structural characteristics and end high-precision positioning requirements. Its motion control process is limited by structural flexible response lag and inertia delay characteristics of traditional control model. In the acceleration / deceleration transition section and end positioning stage, it is prone to position overshoot, structural rebound and difficult to stabilize convergence. Application scenarios include but are not limited to: using high-rise columns 104 and truss cantilever structure, three-dimensional warehouse stacker running in vertical or horizontal long-stroke track; in the stacker with large load / empty change amplitude, the inertia coupling and flexible excitation superposition lead to unstable motion process; in the industrial control stacker scene with limited speed response of the configured driver 103 and long sampling period of the control system.

[0027] It can be understood that the core control strategy of the present application is mainly aimed at the following stacker motion scenarios with typical control challenges, and at least one of the following conditions is met: the stacker structure has low rigidity or long cantilever structure, which has the risk of vibration rebound in the high acceleration or emergency stop motion stage; the inertia deviation and structural elastic lag in the end positioning section cause the problem of not stopping and not stabilizing; S-curve control cannot realize modeling and feedback of structural modal response, and there is a risk of resonance band excitation; the control algorithm relies on a single closed-loop feedback model, and it is difficult to respond to the structural trajectory coupling behavior under complex working conditions.

[0028] It should be noted that the adaptive S-curve generation and frequency domain structural response modeling method proposed in the present application needs to obtain the pre-discrete model or rigid preset condition of the stacker structure in advance, and dynamically complete the selection and correction of the curve form with the vibration response characteristics in the control process as the driving input.

[0029] It is worth noting that the frequency spectrum prediction mapping mechanism and trajectory optimization algorithm proposed in the present application are not dependent on a specific type of stacker structure, driving scheme or path trajectory, and are also applicable to: industrial motion execution scenarios with flexible resonance response of the control system; complex path control with dynamic update of the motion path planning and non-constant inertia model; scenarios where the control output path has resonance sensitive frequency band avoidance requirements and the execution path can be continuously disturbed.

[0030] Referring to Figure 1 , the figure is a schematic diagram of an exemplary application scenario provided by an embodiment of the present application.

[0031] As Figure 1 shown, the present application is applied to a stacker, which comprises a ground rail 100, an overhead rail 101, a base 102 movable along the ground rail 100, a driver 103, a vertical column 104, and a controller 105.

[0032] The ground rail 100 and the overhead rail 101 are arranged below and above the working area of the stacker respectively, forming a guiding channel for the horizontal movement of the stacker. The ground rail 100 supports the load weight of the base 102 and guides its running direction, and the overhead rail 101 is connected to the top of the column 104 to form a rigid closed-loop structure, effectively suppressing lateral sway and improving overall stability.

[0033] The base 102 is arranged on the ground rail 100 and serves as a carrying platform for the horizontal movement of the stacker, and can move forward and backward along the ground rail 100. The base 102 is integrated with a walking driving mechanism and a cable traction device for continuous supply of driving signals and power.

[0034] The column 104 extends vertically upward from the base 102 and penetrates through to the overhead rail 101, forming a cross-bracing structure. The column 104 provides a vertical guide rail for a lifting device of the stacker not shown in the figure, which is usually a lightweight high-strength profile that not only ensures bending stiffness but also has certain flexible response characteristics, and is a key object for dynamic behavior modeling.

[0035] The driver 103 is used to drive the base 102 to move in the horizontal direction.

[0036] In the embodiment not shown in the figure, the driver 103 can be arranged inside the base 102, and can realize high responsiveness and smooth acceleration and deceleration control by combining a servo motor with a gear rack, a ball screw, or other driving mechanisms, or can adjust the speed change through a frequency converter.

[0037] The controller 105 is usually an embedded PLC, an industrial computing platform, or a motion control card, and its main responsibilities include: obtaining user-set target positions and motion parameters; generating a multi-segment S-curve speed trajectory; performing resonance avoidance calculation based on stacker structure modal characteristic identification; performing real-time position error compensation and speed correction, and outputting the final control command to the driver 103.

[0038] It can be understood that the stacker control system can realize full-process control and optimization of the whole machine motion process, especially solving the problems of sway, resonance, and positioning error caused by the inability of traditional trajectory control methods to predict the elastic response of the structure under the conditions of long travel and low rigidity. Figure 1 The structure shown is a typical application scenario in the embodiments of the present application, and in actual application, it can also be extended or adjusted according to the configuration of the stacker system, which is not described herein.

[0039] Referring to Figure 2 The figure is a module schematic diagram of the controller 105 provided by the embodiment of the application.

[0040] Figure 2 It is shown that the controller 105 comprises a curve generation module 1051, a vibration identification module 1052 and an adaptive feedback control module 1053, wherein: the curve generation module 1051 is configured to generate a speed change curve and a position change curve according to a movement target set by a user, and to perform discretization processing on the curves to output a theoretical speed value and a theoretical position value in a control period. The trajectory generation module supports multiple S-curve type generation strategies, and can dynamically select a speed curve of four to seven different forms according to the rigidity level of the stacker structure.

[0041] In an embodiment not shown in the figure, the curve generation module 1051 further comprises a frequency spectrum prediction sub-module configured to input the generated curve into a preset frequency domain model to perform Fourier transform, predict potential excitation frequency bands and perform resonance avoidance curve reconstruction operation.

[0042] The vibration identification module 1052 is configured to judge whether the generated initial speed curve has a risk of causing structural resonance based on a preset structure modal database. The vibration identification module 1052 matches the frequency domain components of the curve acceleration change rate with the stacker structure modal frequency through frequency spectrum excitation map analysis. If a resonance sensitive curve segment is identified, the vibration identification module 1052 performs parameter optimization on the target curve segment through a perturbation optimization algorithm, and outputs an optimized speed curve after resonance suppression, which is used to replace the original curve for subsequent control.

[0043] The adaptive feedback control module 1053 is configured to perform a speed compensation control algorithm based on position deviation. The adaptive feedback control module 1053 compares the real-time feedback stacker position with the theoretical trajectory, calculates the deviation, and generates a speed compensation instruction through a PID control logic. Meanwhile, the adaptive feedback control module 1053 supports structure rigidity level parameter input, can automatically call a preset PID parameter table, and matches and dynamically adjusts the proportional term, integral term and differential term coefficients, thereby improving the sensitivity and stability of the feedback control response, and is particularly suitable for stacker end micro-motion and rebound segment control requirements.

[0044] The aforementioned modules work cooperatively to realize a full-process closed-loop control strategy from trajectory planning, structure modal identification, resonance suppression to real-time error correction, thereby effectively improving the dynamic response and end positioning accuracy of the stacker under long-stroke and low-rigidity structure. The controller 105 can be realized by an industrial-grade embedded platform, has high real-time performance and system integration capability, and is suitable for various medium and large-sized stacker automation equipment.

[0045] Next, a kind of S curve and closed loop motion control method for stacker provided by the embodiment of the application is introduced in conjunction with the drawings, Figure 3 The method shown is applied to a stacker.

[0046] S1: Obtain user setting parameters.

[0047] In the embodiment, the user setting parameters include but are not limited to: target position, target maximum speed, maximum acceleration, jerk, and structural rigidity level. The structural rigidity level is used to reflect the elastic response characteristics of the motion components of the stacker in the acceleration and deceleration stage. Its acquisition method can be based on the cross-sectional size, structural material, connection form and vibration response data in the historical running process of the components of the stacker, and a combination of static analysis and modal experiment modeling is adopted. The introduction of the structural rigidity level enables the subsequent trajectory generation logic to have the ability to cooperate with the specific mechanical structure characteristics, thereby effectively avoiding the structural resonance or secondary shaking phenomenon of high inertia mechanism at the end of the motion stage.

[0048] S2: Generate a speed change curve and a position change curve according to the user setting parameters.

[0049] In the embodiment, the speed change curve is determined according to the curve type corresponding to the structural rigidity level, and is modeled by a function. The number of curve segments can be four, five, six or seven, covering various combination types such as acceleration change rate segment, constant acceleration segment, constant speed segment and deceleration segment. The position change curve is obtained by integrating the speed change curve.

[0050] S3: Discretize the speed change curve and the position change curve to obtain corresponding theoretical speed values and theoretical position values in each control period.

[0051] In the embodiment, the curve is discretized at a high density, and each discrete point corresponds to an executable control period. The discretization accuracy is set according to the end control resolution of the stacker, to ensure that the time resolution of the output control instruction is sufficient to respond to the structural micro-vibration behavior. Through the discretization processing, the continuous trajectory is mapped to a digital control instruction sequence that can be executed in real time.

[0052] S4: Obtain the output rotational speed of the driver 103 according to the theoretical speed value, and obtain the actual position of the stacker according to the output rotational speed. Compare the actual position with the theoretical position value, generate a compensation speed value according to the comparison result, and superimpose the compensation speed value on the theoretical speed value of the current control period to update the output rotational speed.

[0053] In this embodiment, the actual position is obtained through the driver 103 encoder feedback or external displacement sensor, the control logic calculates the error term based on real-time deviation, calls the adaptive PID control algorithm to generate compensation speed value, and superimposes the compensation on the current theoretical speed instruction, and outputs to the driver 103 for execution. In terms of parameter setting, the corresponding preset PID parameter table is called according to the structural rigidity level, and the proportional, integral and differential coefficients are automatically matched to strengthen the response characteristics of the controller 105 to the flexible structure.

[0054] It can be understood that this step is particularly important at the end of the stacker positioning section, which can effectively buffer the rebound effect caused by residual inertia and improve the convergence speed and stability of the final positioning process.

[0055] Before the specific technical content of the unfolding step, the embodiments of the present application need to emphasize again: the typical object targeted by the present application is not a general structure or a standard track motion mechanism, but a stacker type system with one or more of the following characteristics: the structural height exceeds 5 meters, the moving beam adopts thin-walled aluminum alloy or truss design, the moving path covers multiple regional multi-layer shelf systems, and the load end has obvious nonlinear flexible response characteristics; The common characteristics of such structures are: although the motion control unit can complete path planning according to the theoretical trajectory, due to the limited overall rigidity of the mechanism and the existence of elastic hysteresis effect at the connection point, it is easy to induce low-frequency structural response during acceleration and deceleration, especially in the terminal stage, often appearing residual rebound, slow shaking or micro-oscillation phenomenon, causing the final positioning error to be difficult to control within 1mm, affecting the stable operation of the stacker and the accuracy of the goods loading and unloading.

[0056] It should be pointed out that the foregoing problems cannot be completely solved by relying on traditional PID error compensation or prolonging the deceleration section. Because in the flexible dominant structure, there is a nonlinear coupling between the excitation behavior and the trajectory curve, even in the ideal state without external disturbance, only the jerk change of the trajectory itself is enough to form an excitation source and cause resonance.

[0057] It can be understood that the resonance effect described in the application is not caused by external collision, manufacturing error of structure or mechanical loosening behavior caused by single excitation, but due to the continuous change trend of high-order derivative (especially jerk) in the trajectory planning process, periodic and cumulative excitation input is formed near the specific structural modal frequency, thereby forming energy resonance coupling with the inherent elastic modal of the stacker body. This resonance has the characteristics of high certainty, structure dependence and difficulty to suppress by general feedback, which shows that even if the control system strictly follows the theoretical trajectory, displacement amplification, response delay or end oscillation problems will still occur in the specific frequency range. The traditional closed-loop strategy based on position error cannot predict this kind of internally induced excitation mode, resulting in response lag, compensation failure, and finally forming a system positioning unstable state.

[0058] In the embodiment, by obtaining the structural rigidity level, it is no longer assumed that the controlled object is a rigid body or an ideal flexible body, but the structural behavior is taken as a constraint input to intervene in the trajectory design process in advance. The structural rigidity level can be determined by static structural analysis and joint modeling of vibration response in operation, which reflects the dynamic characteristic boundary of the target stacker, and is the basis for subsequent curve segment number, acceleration change rate and feedback gain setting. On this basis, instead of fixedly using traditional 5-segment or 7-segment S-curve, through the preset speed change curve function, the speed change curve that meets the specific excitation frequency avoidance demand can be constructed in the time domain by adjusting the jerk change rate and duration under the premise of meeting the maximum speed and acceleration constraints.

[0059] Further, by using the multiple resonance bandwidth segment information recorded in the structural modal database, the initial trajectory is analyzed in frequency domain and potential excitation segments are identified. This part not only judges whether the deviation from the time domain error analysis, but also includes whether the resonance from the frequency domain behavior, and takes it as an important boundary constraint for iterative optimization of the trajectory.

[0060] Further, in the closed-loop control part, the application is not limited to traditional PID parameter adjustment, and the structural rigidity level is also taken as a partition setting parameter to form a set of PID control parameter table with structural label. When the stacker runs, the matching control gain combination is automatically called according to the structural rigidity level, so as to achieve the effect of stable closed-loop control.

[0061] Next, the principle part of the speed change curve of the method of the application is further expanded.

[0062] It can be understood that, in a typical stacker trajectory control process, in order to achieve smooth start and stop, reduce structural excitation and control impact, the speed change curve is usually described by a piecewise S-shaped curve. The core idea is to control the continuity of the first derivative and the second derivative of the speed change process, so that the whole trajectory has better physical smoothness and dynamic adaptability, avoiding controller 105 output oscillation caused by sudden changes.

[0063] Specifically, the speed change curve includes one of four curve types: four-segment curve, five-segment curve, six-segment curve, and seven-segment curve.

[0064] The four-segment curve includes an acceleration acceleration segment, an acceleration decrease segment, a deceleration increase segment, and a deceleration decrease segment.

[0065] It is easy to understand that the four-segment curve is the simplest form, mainly including two acceleration processes and two deceleration processes. It realizes the rapid lifting and falling of the speed by setting the positive and negative jerk change segments, and is suitable for basic stacking conditions with short travel, light load, and moderate precision requirements. However, this curve has a large jerk change in the acceleration and deceleration stages, which can easily cause impact peaks and may cause mechanical fatigue or vibration during long-term operation.

[0066] The five-segment curve includes an acceleration acceleration segment, an acceleration decrease segment, a uniform speed segment, a deceleration increase segment, and a deceleration decrease segment.

[0067] It is easy to understand that the five-segment curve inserts a uniform speed segment based on the four-segment curve, which can form a speed stable platform in the middle segment. This design is suitable for occasions that require long-distance horizontal movement, and can avoid excessive load adjustment caused by the controller 105 being in a speed regulation state for a long time, and also facilitates the early activation of the deceleration segment to achieve soft stop.

[0068] The six-segment curve includes an acceleration acceleration segment, an acceleration constant segment, an acceleration decrease segment, a deceleration increase segment, a deceleration constant segment, and a deceleration decrease segment.

[0069] It is easy to understand that the six-segment curve further subdivides the acceleration and deceleration processes by adding an acceleration constant segment and a deceleration constant segment. This means that the system runs at a constant acceleration in some stages, making the jerk change more moderate and effectively avoiding structural impact or wheel-rail resonance caused by continuous sudden changes. This type is suitable for stacking mechanisms with certain inertia delay in motion response, especially for stacking machines with large driving inertia.

[0070] The seven-segment curve includes an acceleration acceleration segment, an acceleration constant segment, an acceleration decrease segment, a uniform speed segment, a deceleration increase segment, a deceleration constant segment, and a deceleration decrease segment.

[0071] It is easy to understand that the seven-segment curve is the most complete structure, covering seven stages. The seven-segment curve realizes multi-level controllable adjustment in the three dimensions of speed, acceleration and jerk, and is most suitable for application in the working conditions of the stacker with long travel, heavy load and high positioning requirements, and can significantly improve the predictability of end response and the stability of system adjustment.

[0072] For example, the seven-segment curve can be understood with reference to Figure 4 , Figure 4 is a schematic diagram of the seven-segment curve trajectory of the embodiment of the present application.

[0073] Figure 4 The continuous change process of displacement, speed, acceleration and jerk in the walking movement of the stacker is shown. It is suitable for scenes with high requirements for motion smoothness and structural response control, and is particularly suitable for stacker structures with significant structural flexibility or large inertia variation.

[0074] Figure 4 The speed change curve is composed of seven stages, which are: acceleration acceleration segment ( ), constant acceleration segment ( ), acceleration reduction segment ( ), constant speed segment ( ), deceleration increase segment ( ), constant deceleration segment ( ), and deceleration reduction segment ( ).

[0075] Further, Figure 4 The curve corresponding to the jerk reflects the distribution change of the jerk in the time domain. In the acceleration and deceleration stage, the jerk maintains a constant non-zero value; and in the constant acceleration stage, the jerk is zero. In the embodiment not shown in the figure, the jerk also includes a negative value, which appears in the deceleration stage. By controlling the positive and negative of the jerk, the acceleration is linearly changed when entering and exiting the maximum value, which helps to avoid transient impact caused by sudden change.

[0076] Next, the generation part of the speed change curve of the method of the present application is further expanded.

[0077] For example, the seven-segment curve can be understood with reference to Figure 5 , Figure 5 is a flowchart of a speed change curve generation method of an embodiment of the present application.

[0078] In one example, the speed change curve is generated, including: determining a corresponding curve type according to the target position, the target maximum speed, the maximum acceleration and the jerk; and calculating the speed change curve through a preset speed change curve function according to the curve type. Specifically, the target of generating the speed change curve for the walking section of the stacker is to realize a soft and smooth starting, running and stopping process under the premise of meeting the motion constraint conditions such as the target position, the maximum speed, the maximum acceleration and the jerk, to avoid over-shooting of the driver 103 or structural excitation caused by sudden change of acceleration, and to improve the end positioning accuracy.

[0079] In the embodiment, according to the control theory, when the maximum jerk is known, the change process of the acceleration with time can be obtained by integration, and then the change relationship of the speed with time can be obtained by twice integration. By modeling the motion process as a typical three-segment or multi-segment acceleration change curve, and controlling the acceleration slope of each segment according to the limited value of the jerk, it can be ensured that the entire speed change curve realizes continuous derivative in the starting, speed changing, constant speed and decelerating stages, and avoids mechanical impact caused by sudden change of acceleration.

[0080] Further, in the judgment of the actual curve type, first, the time and displacement required by the theoretical maximum speed are calculated and compared with the target displacement and maximum speed. If the stroke is insufficient to support a complete constant speed segment, the curve is dynamically adjusted to a five-segment or six-segment structure (remove the constant speed segment or compress the acceleration constant segment); if the stroke is sufficient, a seven-segment curve model including a complete acceleration change segment, a constant speed segment and a deceleration change segment can be constructed. In each segment, the duration between segments is calculated according to the target jerk, acceleration and maximum speed, to ensure the continuity of speed and acceleration between segments and to realize the closed segmentation of the entire speed curve.

[0081] Further, the speed change curve function adopts a preset segmented time-acceleration planning model, and the core is the control variable jerk value, which is integrated through the time domain to generate acceleration, speed and displacement data.

[0082] Taking a typical seven-segment curve as an example, the first half is the acceleration process, which includes an acceleration rising segment (jerk is positive), an acceleration maintaining segment (jerk is 0) and an acceleration falling segment (jerk is negative); the middle segment is a constant speed segment (acceleration is 0); and the second half is a symmetrical deceleration process, including a deceleration rising segment (jerk is negative), a deceleration maintaining segment (jerk is 0) and a deceleration falling segment (jerk is positive). In each segment, the controller 105 performs real-time integral operation according to the preset jerk, and sequentially derives the acceleration, speed and position, and performs continuity verification on the boundary conditions of each segment to ensure smooth motion process without sudden change.

[0083] It can be understood that the generation logic of the multi-segment curve of the present application can flexibly match the curve structure according to different stroke lengths and target speeds, so that the motion process takes into account both rapidity and smoothness, and avoids structural vibration or drive saturation caused by improper parameter selection.

[0084] In yet another example, the user-set parameters further include a structural rigidity level of the stacker, which is determined according to the structural dimensions, component materials and historical vibration responses of the stacker.

[0085] It can be understood that the structural rigidity level of the present application refers to a parameterized level identifier for characterizing the anti-deformation capability of the whole structure of the stacker to motion excitation during operation, which essentially reflects the elastic response characteristics of the stacker structure under unit load or excitation.

[0086] It is easy to understand that if the influence of the structural rigidity level is not considered in the process of planning the speed curve, the generated trajectory curve will be seriously mismatched with the dynamic characteristics of the stacker structure itself, which is specifically embodied in the following three aspects.

[0087] Firstly, in the case where the structural rigidity level is not considered, the trajectory curve is often designed based on the target position, maximum speed, maximum acceleration and jerk, etc., with motion performance as the priority, i.e., faster response and shorter running time are pursued. Such design may work normally in a rigid structure, but when applied to a flexible stacker, the weak anti-vibration capability of the flexible stacker will directly excite the modal response of the structure due to frequent acceleration changes or large jerk values, resulting in the problems of amplified end micro-swing, affecting positioning accuracy, rising risk of dynamic resonance, forming stress concentration of the structure, and long-period shaking leading to misjudgment of the closed-loop control and over-compensation phenomenon.

[0088] Secondly, in a flexible stacker, there is often a first-order or second-order modal frequency in the structure, and when the excitation frequency band of the trajectory curve is just near these modal frequencies, a resonance state of strong excitation and weak damping is likely to occur. If no pre-judgment is made according to the structural rigidity level, the generated curve may induce modal coupling in the acceleration and deceleration segments, resulting in low-frequency high-amplitude resonance, and even cumulative effect superimposed in the whole trajectory path.

[0089] Thirdly, the traditional PID control structure mainly deals with the closed-loop internal factors such as actuator lag and error feedback, and is difficult to effectively correct the structural response caused by the excitation of the curve itself. If the jerk of the trajectory itself changes too much, even if the position error is perceived, the controller 105 is also difficult to suppress the structural vibration induced thereby in real time, thereby causing the compensation to induce greater excitation, forming a negative cycle of control amplifying vibration.

[0090] In the embodiment, the dynamic response capability of the stacker structure is pre-embodied in the generation process of the speed curve by taking the structural rigidity level as an intermediate parameter. On this basis, the following key planning parameters can be automatically adjusted: the number of S-curve segments; the maximum jerk and maximum acceleration boundaries; and the time allocation of each segment.

[0091] In some optional embodiments, the determination of the structural rigidity level comprehensively considers the following three types of key elements: the first type of key element is the structural size parameter, including but not limited to the cross-sectional area of the column 104, the aspect ratio, the member support span, and the mounting method. Large size, high cross section, and short cantilever type structures generally have high inherent rigidity, are easy to transfer driving load and suppress low-frequency vibration; the second type of key element is the member material information, such as carbon steel, aluminum alloy, or high-strength alloy steel, etc. The elastic modulus, density, and damping characteristics of the material itself will directly affect the response performance of the overall structure under excitation conditions; the third type of key element is the historical vibration response data. Through the acceleration, position error, vibration spectrum, and other operation monitoring data of the stacker during operation under typical working conditions, combined with frequency domain analysis and modal identification algorithm, the measured natural frequency, main modal shape, and damping ratio of the structure are extracted, which are used to supplement the dynamic evaluation of the structural flexibility.

[0092] As can be appreciated by those skilled in the art, in order to facilitate classification processing, the structural rigidity level is divided into multiple discrete levels, for example: first level (high rigidity), second level (medium rigidity), and third level (low rigidity) three intervals. The controller 105 can automatically select the appropriate speed change curve type, acceleration boundary, and jerk configuration parameters according to the level, to actively adapt to the structure characteristics in the curve planning stage, thereby reducing the risk of excitation.

[0093] Further, the division process of the structural rigidity level can be completed by offline modal testing before the stacker is shipped, or can be dynamically generated by online identification through active excitation and response collection in the early stage of operation. The application does not limit which way is specifically adopted, nor does it limit the division interval and division method of the rigidity level. Any parameterized level definition that can represent the anti-excitation capability of the structure can be regarded as an implementation form of the structural rigidity level in the application.

[0094] Reference Figure 6 , Figure 6 The flowchart of another speed change curve generation method of the embodiment of the application is shown in FIG. 6.

[0095] In another alternative embodiment, generating a speed change curve according to the user setting parameters comprises: S2.1: determining a corresponding curve type according to the target position, target maximum speed, maximum acceleration, and jerk; S2.2: calculating a speed change curve according to the curve type, by using a preset speed change curve function, in combination with a preset spectrum prediction mapping model and the structural rigidity level, wherein the spectrum prediction mapping model is obtained by performing offline modal identification on the stacker, and the offline modal identification comprises extracting inherent modal frequencies, damping ratios, and mode shape distributions of the stacker corresponding to the structural rigidity level in a motion state, to generate a spectrum modal database; in this embodiment, the spectrum prediction mapping model is used to predict a structural response spectrum caused by the speed change curve, and its essence is a modeling mechanism that links a motion excitation to a structural dynamic mode, aiming to predict a resonance frequency band that may be excited in the trajectory planning stage, so as to avoid and optimize in the subsequent curve construction, thereby achieving the purpose of actively suppressing structural vibration.

[0096] In some alternative embodiments, the spectrum prediction mapping model is constructed by the following offline modal identification process: first, at the completion or design stage of the stacker, an excitation experiment is performed on the stacker by using an external excitation source (such as an impact hammer, a swept signal, a pulse response excitation, etc.), and response data is recorded; in another alternative embodiment, finite element modeling technology can be used to simulate and analyze the dynamic characteristics of the stacker structure under different loads, driver 103 actions, and installation states.

[0097] Further, the excitation and response signals are processed in the frequency domain to extract the frequency response function of the structure, and then the inherent modal frequency, damping ratio, and mode shape distribution parameters of the stacker in the working state are obtained.

[0098] These parameters describe the structural amplification factor and reaction path of the stacker under each excitation frequency, and are the core basis for determining the resonance risk.

[0099] Further, the aforementioned inherent modal frequency, damping ratio, and mode shape distribution parameters are established into a database, and the corresponding frequency domain excitation sensitive interval of the stacker is labeled.

[0100] Further, according to the data recorded in the database, a spectrum modal database is constructed, and a Fourier transform algorithm and a perturbation optimization algorithm are configured to generate a spectrum prediction mapping model.

[0101] It can be understood that by constructing the spectrum prediction mapping model, the dynamic resonance risk detection and avoidance suggestion generation can be completed at the initial stage of trajectory planning, without relying on later feedback control or additional sensor configuration. It is particularly suitable for high-speed, long-stroke, flexible structure dominant type stacking scenarios, effectively improving the operation noise immunity and precise positioning ability, and reducing the risk of structural fatigue loss.

[0102] In one example, the specific steps of S2.2 are as follows: S2.2.1: According to the curve type, calculate the initial speed change curve through the preset speed change curve function; Specifically, how to calculate the speed change curve according to the curve type in combination with the preset speed change curve function has been described in the foregoing content, and the present application will not be repeated here.

[0103] S2.2.2: Discretize the initial speed change curve in the time domain to obtain the input parameters of the spectrum prediction mapping model; Specifically, the continuous speed change curve is not convenient for digital signal processing operations such as fast Fourier transform, so it needs to be discretized at equal time intervals to obtain the speed value, its first derivative and second derivative at each control period, thereby forming an input sequence with analysis precision.

[0104] In the present embodiment, the time step of the discretization processing can be set to the consistent sampling time of the control period of the driving controller 105, and the specific step can be adjusted according to the refresh frequency of the driver 103 to ensure the restoration precision of the curve in the time domain. In order to ensure the resolution and amplitude accuracy of the frequency domain results, the sequence length needs to meet the Nyquist sampling theory requirements, and in order to avoid the problem of spectral aliasing, the number of sampling points is generally set to the power of 2 to adapt to the operation efficiency requirements of the fast Fourier transform algorithm. After obtaining the discrete sequence, it is used as the input parameter of the spectrum prediction mapping model for subsequent prediction modeling of the structure response.

[0105] S2.2.3: Perform Fourier transform on the acceleration change rate of the input parameter through the spectrum prediction mapping model to obtain a spectrum excitation map, and obtain a structure excitation frequency band according to the energy density distribution corresponding to each frequency point in the spectrum excitation map; Specifically, the purpose of this step is to map the continuous change of the initial speed change curve in the time domain to the frequency domain to reveal the excitation intensity distribution at different frequencies. Since the stacking machine structure usually has a flexible dominant characteristic, its inherent modal frequency distribution is dense, and there are multiple low-frequency resonance sensitive zones, so it is necessary to analyze the high-order derivative characteristics of the motion curve, especially the frequency components of the acceleration change rate, to determine whether there is a potential resonance excitation risk. The present application performs discrete Fourier transform on the discrete acceleration change rate sequence input through the spectrum prediction mapping model to convert to the frequency domain form and form a spectrum excitation map for further structure response risk matching.

[0106] In the present embodiment, the acceleration rate of change is obtained by two-order time difference operation from the initial speed change curve, and before the discrete sequence processing, a window function is weighted on the input parameters to suppress the sidelobe leakage effect, so as to ensure that the spectral result after Fourier transform can accurately reflect the energy concentration trend of the high-order dynamic characteristics in the curve.

[0107] Further, the spectral prediction mapping model is not simply a Fourier transform calculation, but a standardization calibration of the energy density calculation in the frequency domain according to the typical operating conditions of the stacker structure.

[0108] It can be understood that each frequency point in the frequency spectrum records the corresponding normalized excitation energy value. The normalized excitation energy value is obtained by calculating the power spectral density after squaring the amplitude of the frequency point, and at the same time, the weighting integral is performed in combination with the duration of the frequency band in the speed curve to reflect the strength of the excitation persistence of the frequency band in the actual operation process.

[0109] For example, in a certain speed change curve, if the acceleration rate of change changes continuously near a certain frequency, and the frequency component amplitude is large, then the frequency point and its adjacent frequency band in the frequency spectrum will have an energy peak; otherwise, the frequency band excitation strength is weak, and it does not constitute the main reason for exciting resonance.

[0110] Further, after the generation of the spectral excitation map, according to the structure response identification strategy preset in the present application, all frequency intervals with energy density greater than the noise reference value in the spectral excitation map are further extracted, and a certain range is expanded to both sides with each local peak point as the center to form a structure excitation frequency band. The certain range described in the present application is adjusted according to the modal damping ratio recorded in the stacker structure identification data, and is usually set to 5%-10% of the target modal frequency, which is used to cover the potential resonance bandwidth.

[0111] As can be understood by those skilled in the art, the jerk curve directly reflects the dynamic excitation behavior of the structure system in the control instruction, especially for the long-stroke stacker with low stiffness and large inertia, the structure response is extremely sensitive to the change of the jerk signal. In the traditional motion control system, only the smoothness of the speed curve or the constraint condition of the acceleration is usually concerned, and the strong coupling effect of the jerk on the structure micro-vibration behavior is ignored, which further leads to the overlap of the excitation frequency and the modal frequency caused by the motion planning in the case of low-frequency modal in the structure body, and the risk of structure resonance. The present application constructs the spectral excitation map by Fourier transform, which is essentially a means to predict the structure response risk in advance, and effectively avoids the response lag problem caused by relying only on feedback adjustment.

[0112] S2.2.4: Match the structural excitation frequency band with the structural modal information recorded in the spectral modal database to obtain a curve segment with a risk of exciting resonance, wherein the matching is based on a resonance risk judgment rule to evaluate the natural modal frequency of the structural excitation frequency band and the structural modal information. The resonance risk judgment rule includes: when the energy density of a frequency point in the structural excitation frequency band is greater than or equal to a preset modal threshold, and the corresponding frequency point falls within the resonance sensitive frequency band of a modal frequency, the corresponding curve segment is judged to have a risk of exciting structural resonance. Specifically, the purpose of this step is to identify whether there is a motion segment in the current speed change curve that has the potential to induce structural resonance by matching the structural excitation frequency band extracted from the spectral excitation spectrum with a pre-established structural modal spectrum database. The identification process is not a simple frequency overlap search operation, but a resonance risk assessment logic constructed based on structural resonance theory and actual stacker crane operating conditions, which is used to accurately identify those speed curve segments that couple with the structural natural modal frequency, thereby causing abnormal structural vibration.

[0113] In this embodiment, the structural modal spectrum database is derived from the modal data set constructed by offline modal identification in the aforementioned step S2.2, which records the modal frequency distribution, damping ratio information and corresponding vibration mode of the entire stacker or key parts, and is hierarchically archived according to the structural stiffness level.

[0114] Furthermore, during the actual matching operation, the controller 105 calls the structural excitation frequency band information in the spectrum excitation map and traverses all modal frequencies recorded in the database under the current structural stiffness level. For each modal frequency value, a resonance sensitive frequency band is set in its upper and lower frequency domains. The resonance sensitive frequency band is generally dynamically set according to the damping ratio, aiming to cover the frequency band energy distribution range formed by the expansion of structural damping during the actual structural response process. Subsequently, each frequency point in the spectrum excitation map is cross-compared with the modal frequency band: if a frequency point falls within the resonance band range of the modal frequency and the energy density value corresponding to the frequency point is greater than or equal to the preset modal excitation threshold, then the frequency point is determined to have the potential risk of exciting the modal response. When multiple frequency points meet the above conditions simultaneously, the excitation bandwidth they constitute is further evaluated. If the energy of consecutive frequency points is concentrated and the degree of mode mode matching is high, it can be inferred that the current velocity change curve contains a curve segment that may cause resonance.

[0115] In some optional embodiments, the matching process can further include the following three parameters as reference dimensions: the first parameter is the curve segment duration, if the curve segment duration corresponding to the excitation frequency band is significantly higher than the critical response period of the structural response (generally determined by modal damping), it indicates that the excitation is sufficient to cause the accumulation of structural response and increase the risk of resonance; the second parameter is the curve segment energy gradient, which evaluates the energy change rate of the curve segment on the excitation frequency band, if the energy rising or falling trend coincides with the structural modal response trend, the matching weight is enhanced; the third parameter is the multi-modal superposition, for flexible structures with adjacent or overlapping modal frequencies, if the excitation frequency band crosses multiple modal frequency band regions, the corresponding curve segment should be marked with a higher risk level; in the case of meeting the above three parameters, the controller 105 marks the curve segment, defines it as a curve segment with the risk of exciting structural resonance, and records its start and end time points, excitation main frequency, energy value and matching modal serial number, etc. Key parameters are used for subsequent correction.

[0116] S2.2.5: correcting the curve segment to obtain a speed change curve; specifically, the purpose of this step is to reconstruct the speed change curve based on the curve segment identified as having the risk of exciting structural resonance, so as to meet the original motion target constraint conditions while avoiding significant excitation in the structural modal frequency sensitive band, thereby reducing the probability of exciting structural resonance.

[0117] In one example, the specific steps of S2.2.5 are as follows: S2.2.5.1: reconstructing the parameters of the curve segment by a perturbation optimization algorithm, the parameters including the acceleration change rate corresponding to the curve segment, the curve segment duration and the start and end speed values in the curve segment, wherein the perturbation optimization algorithm is configured as a nonlinear search algorithm based on genetic mechanism, the nonlinear search algorithm includes population initialization, fitness evaluation, crossover operation, mutation operation and termination judgment, the fitness function in the fitness evaluation is the spectral excitation energy integral value corresponding to the structural excitation frequency band, and the termination judgment takes the convergence of the fitness function to a preset termination threshold as the judgment condition; specifically, when it is detected that one or more curve segments in the target speed change curve have the risk of exciting structural modal resonance, in order to avoid such excitation behavior causing elastic oscillation or mechanical shaking of the whole or partial structure of the stacker, the multiple key control parameters of the corresponding curve segment need to be reconstructed.

[0118] It can be understood that, since the resonance response shows high sensitivity to energy density in the frequency domain, and the structure has differentiated response characteristics to excitation of different frequency bands, linear adjustment of only a single parameter cannot effectively avoid modal excitation path.

[0119] In the present embodiment, the perturbation optimization algorithm is centered on the optimization index of minimizing the excitation spectral energy, and particularly focuses on the energy projection behavior of the optimized curve segment near the structural modal frequency.

[0120] In one embodiment, the adjustable parameters need to be modeled and constrained first.

[0121] The parameters to be optimized in the present application mainly include: the acceleration change rate in the curve segment, i.e. the transformation rate of acceleration in unit time; the curve segment duration, i.e. the running cycle length of the curve segment; and the start and end speed values in the curve segment, i.e. the speed boundary conditions of the curve segment. These parameters are in a complex coupling relationship in the curve segment, which not only determines the macro profile of the curve, but also directly affects the energy distribution mode of the acceleration derivative signal in the frequency domain.

[0122] In another embodiment, a population initialization operation is first performed. The population initialization defines an initial solution set containing multiple individuals, each individual being a combination of a specific parameter configuration. The initialization process can adopt a distribution sampling strategy based on historical curve experience, combined with a multi-point perturbation mechanism to improve the coverage ability of the parameter space. No screening is performed in this stage, only to ensure that each set of parameters is valid in the constraint space.

[0123] In yet another embodiment, a fitness evaluation operation is performed, and the fitness function is the spectral excitation energy integral value corresponding to the structural excitation frequency band. This value can be obtained by deriving the acceleration curve from the speed change curve constructed by the current individual parameters, and inputting it into the preset spectral prediction mapping model to perform Fourier transform to obtain its frequency spectrum. The total energy distribution in the modal frequency window in the frequency spectrum is counted as the fitness value of the individual. The higher the energy value, the higher the possibility of exciting the structural modal resonance with this set of parameters, and the worse the fitness value. The fitness evaluation process will calculate all individuals one by one in each generation of population to ensure that the selection process is goal-oriented.

[0124] In still another embodiment, the stages corresponding to the crossover operation and the mutation operation are entered. The crossover operation is used to simulate the gene exchange mechanism in natural genetics, and the parameters of individuals with excellent fitness are exchanged to generate new candidate solution individuals, enhancing the global exploration ability of the algorithm. The mutation operation introduces random perturbation to the individual parameters to break out of the local optimal trap with a small probability, improving the ability of the algorithm to jump out of the local extreme value. In the present embodiment, the mutation method adopts a Gaussian perturbation model, i.e. adding a small offset value conforming to Gaussian distribution to a certain parameter value. The crossover and mutation rates can be adjusted in real time according to the population diversity. If the population tends to converge, the mutation probability is increased to introduce new solution candidates.

[0125] In the last embodiment, all the generated new generation individuals will enter the fitness evaluation process again and compete with the high fitness individuals in the last generation population. This process is iterated repeatedly until the preset termination condition is reached. In this application, the termination condition is that the convergence degree of the fitness function reaches a threshold, that is, the fitness function of the optimal individual in the continuous several generations has no significant improvement, or the optimal value is less than the minimum allowable upper limit of the modal excitation energy.

[0126] It is easy to understand that the perturbation optimization algorithm has the multi-peak search characteristic, can avoid falling into a single solution space, and is suitable for solving the non-convex target problem existing in the spectrum avoidance type problem. Its advantage is that it can optimize the nonlinear, discontinuous or irregular solution space without relying on the gradient information of the model, and is particularly suitable for processing the multi-variable, strong coupling and high-dimensional speed curve reconstruction problem. Through the foregoing optimization process, one or more groups of parameter configurations with energy suppression effect in the modal excitation frequency band are finally obtained.

[0127] S2.2.5.2: According to the reconstructed parameters, the initial speed change curve is optimized to obtain a plurality of candidate speed change curves, and the candidate speed change curves are input into the frequency spectrum prediction mapping model to obtain the frequency spectrum excitation spectrum corresponding to each candidate speed change curve. Specifically, after obtaining the curve segment control parameters solved by the genetic mechanism perturbation optimization algorithm, in order to further improve the energy distribution characteristics of the overall speed trajectory outside the structural modal frequency band, the structure of the entire initial speed change curve needs to be optimized based on the parameter combination, and a plurality of selectable speed change curve candidate sets are formed.

[0128] In this embodiment, the curve optimization process takes the perturbation optimization result as the initial solution to perform parameter-driven function reconstruction on the corresponding curve segment. The reconstruction process follows the following control logic: first, the input start and end speed values are taken as boundary conditions, and the curve segment is fitted with a seven-segment (or corresponding type) speed model in combination with the curve segment duration and acceleration change rate generated by the optimization algorithm. Each speed model is constructed based on a cubic or quintic spline function to meet the requirements of continuous connection of speed, acceleration and jerk between segments, avoid non-smooth transitions in the time domain, and ensure the physical realizability of the trajectory.

[0129] Further, after the curve is constructed, the derivative of each candidate speed change curve is calculated to obtain its complete acceleration change rate curve, and sampling discretization processing under a unified time reference is performed, which is input into the preset frequency spectrum prediction mapping model in this application to perform Fourier transform operation to obtain its frequency spectrum excitation spectrum.

[0130] To further ensure the minimization of excitation spectral energy in the vicinity of the modal frequency, the spectral excitation pattern corresponding to each candidate curve is compared with the previously constructed structural modal frequency band one by one and scored. The scoring criteria mainly include two parts: first, the total value of energy in the modal frequency band, that is, the sum of the energy density of the frequency points in the frequency band is calculated; second, the Euclidean distance from the center point of the modal frequency to the frequency at which the excitation peak value is located, which is used to measure whether the current excitation is away from the sensitive area. The above two indicators are constructed into a scoring function by weighted weighting, and the excitation risk score of the corresponding candidate curve is obtained.

[0131] It should be noted that in actual deployment, the number of curves, parameter perturbation range and sampling accuracy can be adjusted according to the device running characteristics, controller 105 performance and structural response model, to ensure sufficient solution space coverage without introducing system load.

[0132] S2.2.5.3: Select the candidate speed change curve with the maximum Euclidean distance from the natural modal frequency and the minimum total spectral energy in the corresponding spectral excitation pattern from the candidate speed change curves as the correction result of the initial speed change curve, and generate a speed change curve; Specifically, according to the excitation risk score obtained above, determine the corresponding candidate speed change curve, and generate a speed change curve by taking the candidate speed change curve as the correction result of the initial speed change curve.

[0133] Next, the part of the method of the present application related to closed-loop control is further expanded.

[0134] Specifically, in the operation process of the stacker, in order to ensure that the displacement trajectory executed by it is consistent with the preset S-curve path, it is necessary to continuously and real-time adjust its motion state by means of closed-loop control logic. Closed-loop control can dynamically correct the output according to the actual feedback during the motion process, thereby effectively dealing with the tracking errors caused by structural elasticity, mechanical clearance, motor response delay, load disturbance, etc., and avoiding overshoot, rebound or jitter phenomenon of the stacker in rapid motion or end positioning.

[0135] In the embodiment, the closed-loop control logic is implemented by the driver 103 and the controller 105, the controller 105 is responsible for trajectory planning and feedback error calculation, and the driver 103 is responsible for actual speed output and motor driving command execution, wherein: the controller 105 first performs time discretization processing on the generated speed change curve and position change curve, and converts them into theoretical speed values and theoretical position values in a discrete control period, to ensure the executability in the control period; the controller 105 issues a target speed command to the driver 103 based on the theoretical speed value of the current period, and the driver 103 controls the stacker motor to operate according to the speed command; the controller 105 synchronously reads the encoder position information fed back by the driver 103, calculates the actual displacement speed in combination with the time period, and compares it with the current theoretical position value; according to the deviation value of the actual position and the theoretical position, the controller 105 calculates a set of speed increments (i.e. compensation speed values) for error compensation through the built-in PID control algorithm, and the compensation amount is used to correct the speed command of the next period, so as to realize closed-loop tracking.

[0136] In some optional embodiments, the three control coefficients (proportional term P, integral term I, and differential term D) of the PID control algorithm used can be adaptively set according to the structural rigidity level of the stacker, to enhance the stability and rapidity of the system response. For example, for a structure with lower rigidity, the P value can be appropriately reduced to avoid over-regulation, the I term is strengthened to prevent residual error lag, and the D term is used to offset dynamic error fluctuations; and for a structure with high rigidity, the P value can be increased to speed up convergence, and the D term is used for dynamic vibration absorption.

[0137] In one example, the acceleration time and deceleration time of the driver 103 are set as the minimum time unit supported by the driver 103.

[0138] In another example, comparing the actual position with the theoretical position value, and generating a compensation speed value to be superimposed on the theoretical speed value of the current control period according to the comparison result, comprises: according to the deviation between the actual position and the theoretical position value, generating a compensation amount for correcting the speed command through a PID control algorithm, superimposing the compensation amount on the theoretical speed value corresponding to the current control period to generate an updated speed command and sending it to the driver 103, wherein the parameters of the proportional term, the integral term and the differential term in the PID control algorithm are adjusted according to the deviation.

[0139] In one example, the controller 105 switches to a micro-motion vibration suppression control mode when the stacker approaches the end positioning interval of the target position (the end positioning interval can be determined by experiments by those skilled in the art), specifically including: in the end positioning interval, the target speed change curve is re-discretized, the discrete frequency is increased to generate a dense control point sequence, and the speed command is output based on the control point sequence; in the micro-motion vibration suppression control mode, the controller 105 constructs an anti-rebound control logic, specifically including: setting a symmetric speed reverse dead zone threshold, prohibiting the controller 105 from outputting control instructions opposite to the main direction when the feedback position produces a short reverse deviation, to avoid secondary reverse shaking caused by excessive adjustment, wherein the feedback position refers to the position of the stacker when the speed needs to be adjusted; superimposing a dynamic damping coefficient for high-frequency oscillation attenuation on the speed command, the dynamic damping coefficient is adaptively adjusted according to the oscillation frequency and amplitude of the feedback speed, and an equivalent speed oscillation absorber is constructed; when the feedback position remains within the positioning window for two consecutive control periods and the speed approaches zero, the controller 105 generates a positioning completion identifier and controls the driver 103 to enter a braking state.

[0140] In one example, the present application provides an S-curve and closed-loop motion control system for a stacker, the system comprising: a trajectory generation module for generating a speed change curve and a position change curve according to user-set parameters, and discretizing the speed change curve and the position change curve to obtain theoretical speed values and theoretical position values corresponding to each control period; a spectrum analysis module for performing frequency domain conversion on the initial speed change curve based on a frequency spectrum prediction mapping model after generating the initial speed change curve, identifying curve segments that have a risk of exciting structural resonance, and combining frequency spectrum modal database information to perform resonance matching and judgment; a trajectory optimization module for performing parameter reconstruction of the curve segments that have a risk of resonance based on a perturbation optimization algorithm, generating a plurality of candidate speed change curves, and selecting the speed change curve from the candidate speed change curves; an adaptive control module for executing closed-loop PID control according to the theoretical speed values and the feedback position deviation, generating a speed compensation quantity and superimposing it on the theoretical speed values, and outputting the updated speed command to the stacker driver 103.

[0141] Although the embodiments of the present application have been shown and described above, it should be understood that the above-described embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above-described embodiments within the scope of the present application.

Claims

1. An S-curve and closed-loop motion control method for a stacker crane, characterized in that: The stacker includes a controller and a driver, and the method includes: Get user setting parameters; generating a speed change curve and a position change curve according to the user-set parameters, wherein the speed change curve is determined according to a preset speed change curve function, and the position change curve is obtained by integrating the speed change curve; Discretizing the speed change curve and the position change curve to obtain corresponding theoretical speed values ​​and theoretical position values ​​within each control cycle; The output speed of the driver is obtained according to the theoretical speed value, and the actual position of the stacker is obtained according to the output speed. The actual position is compared with the theoretical position value, and a compensation speed value is generated according to the comparison result and superimposed on the theoretical speed value of the current control cycle to update the output speed.

2. The S-curve and closed-loop motion control method for a stacker according to claim 1, characterized in that: The speed change curve includes at least one of four curve types, namely, a four-segment curve, a five-segment curve, a six-segment curve and a seven-segment curve, wherein the four-segment curve includes an acceleration acceleration segment, an acceleration reduction segment, a deceleration increase segment and a deceleration reduction segment; the five-segment curve includes an acceleration acceleration segment, an acceleration reduction segment, a uniform speed segment, a deceleration increase segment and a deceleration reduction segment; the six-segment curve includes an acceleration acceleration segment, an acceleration constant segment, an acceleration reduction segment, a deceleration increase segment, a deceleration constant segment and a deceleration reduction segment; and the seven-segment curve includes an acceleration acceleration segment, an acceleration constant segment, an acceleration reduction segment, a uniform speed segment, a deceleration increase segment, a deceleration constant segment and a deceleration reduction segment.

3. The S-curve and closed-loop motion control method for a stacker according to claim 2, characterized in that: The user-set parameters include a target position, a target maximum speed, a maximum acceleration, and a jerk. Generating a speed change curve according to the user-set parameters includes: Determining a corresponding curve type according to the target position, target maximum speed, maximum acceleration, and jerk; According to the curve type, a speed change curve is calculated using a preset speed change curve function.

4. The S-curve and closed-loop motion control method for a stacker according to claim 1, characterized in that: The acceleration time and deceleration time of the driver are set to the minimum time unit supported by the driver.

5. The S-curve and closed-loop motion control method for a stacker according to claim 4, characterized in that: Comparing the actual position with the theoretical position value, and generating a compensation speed value based on the comparison result to be added to the theoretical speed value of the current control cycle, including: According to the deviation between the actual position and the theoretical position value, a compensation amount for correcting the speed instruction is generated by the PID control algorithm, and the compensation amount is added to the theoretical speed value corresponding to the current control cycle to generate an updated speed instruction to be sent to the driver, wherein the parameters of the proportional term, integral term and differential term in the PID control algorithm are adjusted according to the deviation.

6. The S-curve and closed-loop motion control method for a stacker according to claim 3, characterized in that: The user-set parameters also include a structural rigidity level of the stacker, which is determined based on the structural dimensions, component materials, and historical vibration responses of the stacker. The method further includes: According to the curve type, the speed change curve is calculated by using a preset speed change curve function, combined with a preset spectrum prediction mapping model and the structural rigidity level, wherein the spectrum prediction mapping model is obtained by performing offline modal identification on the stacker, and the offline modal identification includes extracting the natural modal frequency, damping ratio and vibration mode distribution of the structural rigidity level corresponding to the stacker in the motion state to generate a spectrum modal database.

7. The S-curve and closed-loop motion control method for a stacker according to claim 6, characterized in that: The speed change curve is calculated by using a preset speed change curve function in combination with a preset spectrum prediction mapping model and the structural rigidity level, including: Calculating an initial speed change curve according to the curve type using a preset speed change curve function; The initial velocity change curve is subjected to time domain discretization processing and used as input parameters of the spectrum prediction mapping model; Performing Fourier transform on the acceleration change rate of the input parameter through the spectrum prediction mapping model to obtain a spectrum excitation spectrum, and obtaining a structural excitation frequency band based on the energy density distribution corresponding to each frequency point in the spectrum excitation spectrum; Matching the structural excitation frequency band with the structural modal information recorded in the spectral modal database to obtain a curve segment with a risk of exciting resonance, wherein the matching is based on a resonance risk judgment rule to evaluate the natural modal frequencies of the structural excitation frequency band and the structural modal information, wherein the resonance risk judgment rule includes: when an energy density of a frequency point in the structural excitation frequency band is greater than or equal to a preset modal threshold, and the corresponding frequency point belongs to a resonance sensitive frequency band range of a modal frequency, determining that the corresponding curve segment has a risk of exciting structural resonance; The curve segment is corrected to obtain a speed change curve.

8. The S-curve and closed-loop motion control method for a stacker according to claim 7, characterized in that: The curve segment is corrected to obtain a speed change curve, including: Reconstructing parameters of the curve segment using a perturbation optimization algorithm, wherein the parameters include an acceleration change rate corresponding to the curve segment, a duration of the curve segment, and start and end speed values ​​within the curve segment, wherein the perturbation optimization algorithm is configured as a nonlinear search algorithm based on a genetic mechanism, and the nonlinear search algorithm includes population initialization, fitness evaluation, crossover operation, mutation operation, and termination judgment, wherein the fitness function in the fitness evaluation is an integral value of the spectrum excitation energy corresponding to the structural excitation frequency band, and the termination judgment is determined based on whether the fitness function converges to a preset termination threshold; Optimizing the initial speed change curve according to the reconstructed parameters to obtain a plurality of candidate speed change curves, inputting the candidate speed change curves into the spectrum prediction mapping model to obtain a spectrum excitation spectrum corresponding to each candidate speed change curve; A candidate speed change curve having the largest Euclidean distance to the natural modal frequency and the smallest total spectrum energy in the corresponding spectrum excitation spectrum is selected from the candidate speed change curves as a correction result of the initial speed change curve to generate a speed change curve.

9. The S-curve and closed-loop motion control method for a stacker according to claim 5, characterized in that: The actual position is compared with the theoretical position value, and a compensation speed value is generated according to the comparison result and added to the theoretical speed value of the current control cycle, further comprising: Get the structural rigidity level of the stacker crane; According to the structural rigidity level, a preset PID control parameter table corresponding to the structural rigidity level is called to set coefficient values ​​of the proportional term, the integral term and the differential term.

10. An S-curve and closed-loop motion control system for a stacker, used to implement an S-curve and closed-loop motion control method for a stacker according to any one of claims 1 to 9, characterized in that: The system comprises: The trajectory generation module is used to generate a speed change curve and a position change curve according to the user-set parameters, and to perform discrete processing on the speed change curve and the position change curve to obtain the theoretical speed value and the theoretical position value corresponding to each control cycle; The spectrum analysis module is used to convert the generated initial velocity change curve into the frequency domain based on the spectrum prediction mapping model, identify curve segments with the risk of exciting structural resonance, and perform resonance matching and judgment based on the spectrum modal database information; a trajectory optimization module, configured to perform parameter reconstruction based on a disturbance optimization algorithm on a curve segment with resonance risk, generate a plurality of candidate speed change curves, and screen the candidate speed change curves to obtain a speed change curve; The adaptive control module is used to perform closed-loop PID control based on the theoretical speed value and the feedback position deviation, generate a speed compensation in real time and add it to the theoretical speed value, and output the updated speed command to the stacker driver.

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