Control system and method of self-walking insulating lifting platform

Abstract

The invention relates to the field of high-altitude operation equipment and automatic control, and discloses a control system and method for a self-walking insulating lifting platform, and the system comprises a posture sensing module which is used for collecting the inclination angle and angular velocity information of the platform in real time; the dynamic modeling module is used for establishing a multi-degree-of-freedom dynamic model of the platform; the optimal control module is used for calculating optimal control input through objective function optimization; and the robust control module is used for realizing anti-interference leveling of the platform under an external disturbance condition based on a sliding mode control algorithm and in combination with adaptive gain adjustment. The method comprises the steps of obtaining real-time attitude information of a platform, establishing a multi-degree-of-freedom dynamic model, defining a weighted objective function and solving optimal control input, calculating control input based on a sliding mode control algorithm, and adjusting the positions of platform supporting legs to achieve a stable leveling state. According to the invention, the leveling precision and the anti-interference capability of the platform are improved, and the method is suitable for safe and stable operation under various complex terrain conditions.

Description

Technical Field

[0001] The invention relates to the field of aerial work equipment and automatic control technology, and in particular to a control system and method for a self-propelled insulating lifting platform. Background Art

[0002] In the current high-altitude operations and live maintenance processes, self-propelled insulated lifting platforms have become important operating equipment, especially in the fields of electricity, communications, construction, etc., and are widely used in complex terrain and high-altitude working environments. In order to ensure operational safety, the design of such platforms must not only realize the basic functions of vertical lifting, but also ensure that the platform can move stably during driving and maintain a stable operating posture under different terrain conditions. However, the existing lifting platform leveling control system often lacks stability and accuracy when facing complex terrain, external disturbances and uncertain factors.

[0003] Traditional leveling control systems are mostly based on simple tilt sensors and hydraulic leveling controls. Although they can basically meet the leveling requirements on flat ground, on complex terrain, due to ground undulations and uneven support, the platform's tilt state will fluctuate significantly, making it impossible to achieve high-precision leveling. Especially during platform travel, traditional systems are unable to respond to rapidly changing terrain and external interference in real time, which can easily lead to posture instability and pose safety hazards to operators. At the same time, existing systems usually lack effective anti-interference control strategies and only maintain balance through passive adjustment of hydraulic legs, making it difficult to meet the stability requirements of the platform under external disturbances such as tilt and vibration.

[0004] In addition, most existing leveling systems lack the ability to adapt to complex terrains, and the outrigger adjustment is not well coordinated with the overall posture of the platform. When the platform is traveling on multiple inclined surfaces or rugged terrain, it is difficult for the system to dynamically adjust the reaction force of the outriggers according to the posture of the platform, resulting in poor leveling effect. These shortcomings limit the flexibility of the platform on different terrains and affect the safety and operating efficiency of the lifting platform. Therefore, there is an urgent need for a control system that can stably level in complex terrains and has anti-interference capabilities to improve the operating stability and safety of the platform. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a control system and method for a self-propelled insulated lifting platform, which can achieve automatic leveling and anti-dumping under complex terrain and external disturbance conditions to improve the stability and safety of the lifting platform.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a control system for a self-propelled insulating lifting platform, comprising:

[0007] The posture perception module is used to collect the tilt angle and angular velocity of the platform in real time;

[0008] Dynamic modeling module, used to establish a multi-degree-of-freedom dynamic model of the platform to describe the center of gravity position and outrigger forces of the platform on complex terrain;

[0009] The optimal control module is used to calculate the optimal control input to minimize the leveling error of the platform;

[0010] The robust control module, based on the sliding mode control algorithm, realizes the anti-disturbance leveling of the platform under external disturbance conditions.

[0011] Preferably, the posture sensing module includes a multi-axis tilt sensor array, and the sensor array includes a three-axis accelerometer and a three-axis gyroscope, which are used to obtain the tilt angle and angular velocity information of the platform in the front-back direction and the left-right direction, and fuse the data through a weighted average method.

[0012] Preferably, the dynamic modeling module is used to construct a nonlinear multi-degree-of-freedom dynamic model, including:

[0013] A center of mass modeling unit is used to determine the three-dimensional position of the center of gravity of the platform to describe the distribution of the center of gravity of the platform on uneven ground;

[0014] The outrigger mechanics unit is used to calculate the reaction force of each outrigger so that the platform can maintain dynamic balance in the forward and backward tilt and left and right tilt directions;

[0015] The coupling modeling unit between the legs is used to calculate the interaction force between the legs to adapt to complex terrain.

[0016] Preferably, the leg mechanical unit determines the reaction force of the legs according to the elastic coefficient and damping coefficient of each leg to ensure that the legs can adjust the platform posture when subjected to force.

[0017] Preferably, the dynamic modeling module establishes a nonlinear equilibrium relationship of the leg forces according to the following conditions:

[0018] At different tilt angles of the platform, the reaction force of the outriggers is proportional to the moment of inertia of the platform to maintain the stability of the platform in the forward and backward tilt and left and right tilt directions.

[0019] Preferably, the optimal control module includes:

[0020] An objective function unit, used for defining a weighted objective function of a leveling error and an outrigger force control error, so as to minimize the leveling error of the platform in a front-to-back direction and a left-to-right direction;

[0021] The optimal strategy unit solves the optimal value of the objective function through a numerical iteration method and is used to output the optimal control input of the platform legs.

[0022] Preferably, the objective function defined by the objective function unit includes the leveling error and the square sum of the outrigger contact force error, and the objective function is used to minimize the leveling error of the platform under complex terrain conditions.

[0023] Preferably, the robust control module comprises:

[0024] The sliding mode control unit is used to define the sliding mode surface of the platform in the forward and backward tilting and left and right tilting directions, and realize the rapid leveling of the platform through the sliding mode control law;

[0025] Adaptive gain unit, used to automatically adjust the sliding mode control gain according to the change of platform inclination error to enhance the anti-disturbance performance of the system;

[0026] The coupling compensation unit is used to reduce the dynamic coupling effect in the front-to-back tilt and left-to-right tilt directions.

[0027] Preferably, the sliding mode control unit adjusts the sliding mode surface response speed through a nonlinear gain, and the parameters of the gain adjustment include:

[0028] The adaptive gain calculated based on the current posture of the platform and external disturbance conditions enables the system to maintain rapid response capabilities in dynamic environments.

[0029] The present invention also provides a control method for a self-propelled insulating lifting platform, comprising the following steps:

[0030] Obtain the real-time attitude information of the platform, and obtain the front and rear tilt angle, left and right tilt angle and angular velocity of the platform;

[0031] A multi-degree-of-freedom dynamic model is established based on the center of gravity position of the platform and the force on the outriggers, and the reaction force of each outrigger is determined by the elasticity and damping coefficient of the outriggers;

[0032] Define a weighted objective function, including the leveling error and the outrigger force control error, and solve the optimal control input according to the objective function;

[0033] The control input is calculated based on the sliding mode control algorithm, and the platform's anti-disturbance is achieved through adaptive gain adjustment and dynamic coupling compensation;

[0034] Based on the calculated control input, the platform outrigger position is adjusted to keep the platform in a stable leveled state on complex terrain.

[0035] The present invention provides a control system and method for a self-propelled insulating lifting platform, which has the following beneficial effects:

[0036] 1. Through the combination of the attitude sensing module and the multi-degree-of-freedom dynamic model, the present invention can obtain the accurate attitude information of the platform in real time and establish an accurate mechanical model. Such a platform has higher leveling accuracy and can remain stable on a variety of complex terrains, thereby effectively reducing the risk of tilt and imbalance.

[0037] 2. The robust control module in the present invention adopts sliding mode control algorithm and adaptive gain adjustment, and further improves the platform's anti-disturbance through dynamic coupling compensation. When the platform is affected by external disturbances or rapidly changing terrain, the control system can respond in time to quickly restore the platform to a stable state, thereby enhancing the system's anti-disturbance effect.

[0038] 3. The present invention realizes dynamic adaptive leveling through the optimal control module, and calculates the optimal control input according to the weighted optimization of the objective function, so that the platform can autonomously adjust the outrigger position and reaction force under different terrain conditions, ensuring that the platform can maintain a horizontal state when moving or staying, and has stronger adaptability.

[0039] 4. The control method of the present invention optimizes the objective function of the optimal control module to balance the force control of the outriggers with the leveling error to reduce unnecessary energy consumption. By precisely regulating the force distribution of the outriggers, the platform effectively saves power consumption during system operation while maintaining stability, and extends the endurance of the equipment.

[0040] 5. The automatic leveling and anti-dumping control method provided by the present invention enables the platform to remain stable during live or high-altitude operations and is not easily affected by terrain or external disturbances. The system promptly performs leveling and correction when the tilt exceeds the safety threshold, thereby improving the safety of the operation process and reducing the risk of operators. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic diagram of the system architecture of the present invention;

[0042] Figure 2 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] Please refer to the attached Figure 1The embodiment of the present invention provides a control system for a self-propelled insulated lifting platform, which is intended to achieve automatic leveling and anti-dumping control of the platform on complex terrain to enhance the stability and safety of the platform. The control system enables the platform to remain stable in different terrain environments and effectively respond to external disturbances through the collaborative work of multiple modules. The following is a detailed description of each module of the present invention.

[0045] Posture perception module

[0046] The attitude perception module obtains the attitude information of the platform in real time, namely the front and rear tilt angles, left and right tilt angles and corresponding angular velocity information, providing key real-time data input for subsequent dynamic modeling and control modules. The attitude perception module integrates data from multiple sensors to enable the platform to maintain real-time attitude information updates under different terrains and different motion states, thereby ensuring that the control system can respond to attitude changes and adjust the balance state of the platform in a timely manner.

[0047] In this embodiment, the attitude sensing module is implemented by a multi-axis tilt sensor array, including but not limited to a three-axis accelerometer and a three-axis gyroscope. In general, the accelerometer is used to obtain the static tilt angle information of the platform, while the gyroscope is used to obtain the dynamic angular velocity information. By using the accelerometer and the gyroscope together, this module can effectively obtain the tilt angle of the platform in the front-to-back direction and the left-to-right direction (respectively expressed as θ x and θ y ) and angular velocity (respectively represented as ω x and ω y ). This information provides key input for subsequent leveling and control.

[0048] In one possible implementation, a three-axis accelerometer and a three-axis gyroscope are respectively installed at the center of mass of the platform to directly measure the attitude information of the platform. The output of the three-axis accelerometer can be used to determine the static tilt angle of the platform, that is, to determine the tilt direction and amplitude of the platform through the direction of the earth's gravity. Specifically, the accelerometer can measure the acceleration components of the platform on the x, y, and z axes, and the relationship between these components and the gravitational acceleration can be used to calculate the static tilt angle of the platform. Assume that the outputs of the three-axis accelerometer are a x 、a y and a z , then the inclination angle can be obtained according to the following relationship:

[0049]

[0050] As an option, in order to improve the accuracy of posture perception, the posture perception module also fuses the data of the accelerometer and gyroscope to obtain more accurate posture information. When the posture changes dramatically, the angular velocity information is more important, while in the static state, the inclination information of the accelerometer is the key. Therefore, in the specific implementation, the system can perform weighted processing on the data in different states. For example, when the posture is stable, the accelerometer data has a higher weight, while in the case of rapid movement or large terrain changes, the reliance on the gyroscope angular velocity data is increased.

[0051] In some embodiments, to improve the accuracy of data fusion, a weighted average or complementary filtering method may be introduced. In one possible implementation, the weighted average fusion method performs time weighting on the data of the gyroscope and the accelerometer. Specifically, the weight W is set to g and W a , corresponding to the weights of the gyroscope and accelerometer data, respectively, and the total weight satisfies W g +W a =1. Combining the time constant and sensor characteristics, the formula can be used:

[0052] θ fused =W g ·θ gyro +W a ·θ accel

[0053] Among them, θ gyro and θ accel are the inclination measurement values ​​of the gyroscope and accelerometer respectively, and the fused inclination information θ is obtained by weighted combination fused .

[0054] In another possible implementation, complementary filtering can be used to dynamically adjust the data. Specifically, complementary filtering is a filtering method that combines low-pass filtering and high-pass filtering to jointly process accelerometer and gyroscope data. The accelerometer data is low-pass filtered to remove noise, which is suitable for low-frequency static tilt detection, while the gyroscope data is high-pass filtered to capture fast dynamic information of attitude changes. The attitude calculation expression of complementary filtering is:

[0055] θ fused (t) = α(θ fused (t-1)+θ gyro (t)·Δt)+(1-α)·θ accel (t)

[0056] Among them, α is the filter coefficient and Δt is the sampling period. By adjusting the value of α, the fusion optimization of sensor data can be achieved to adapt to different terrain and posture change requirements.

[0057] In some embodiments, the attitude perception module can further combine the adaptive filtering mechanism to dynamically adjust the fusion parameters according to the rate of change of the platform attitude. For example, when the platform inclination changes rapidly, the system will increase the weight of the gyroscope data to improve real-time performance; when the inclination changes less or the platform is stationary, the weight of the accelerometer data will be increased to ensure the static accuracy of the attitude. In a specific implementation, the adaptive filtering can be achieved by real-time monitoring of the threshold control of the attitude change rate, thereby achieving adaptive adjustment of the sensor data fusion process.

[0058] In general, the sensor data update frequency of the attitude perception module should meet the requirements of dynamic leveling of the platform, and the typical update frequency can be between 100Hz and 200Hz. In complex terrain, such as when the platform passes through a slope or uneven ground, the attitude perception module can automatically increase the data collection and update frequency to enhance the real-time performance and response speed of the data.

[0059] The attitude perception module of this embodiment provides high-precision, real-time inclination and angular velocity information, providing basic data support for subsequent dynamic modeling and control modules, so that the platform can always maintain stable attitude information updates in complex terrain.

[0060] Dynamic Modeling Module

[0061] The dynamic modeling module is used to establish a multi-degree-of-freedom dynamic model of the platform, which describes in detail the center of gravity position of the platform in complex terrain, the force relationship of the legs, and the coupling characteristics between the legs. The main purpose of this module is to provide an accurate mechanical model and provide dynamic parameter input for the subsequent control module, so that the platform can achieve leveling and anti-dumping functions. By establishing a multi-degree-of-freedom model, this module ensures the stability of the platform on complex terrain, and provides basic dynamic support for optimal control and robust control.

[0062] In this embodiment, the dynamic modeling module specifically includes a center of mass modeling unit, a leg mechanics unit, and a leg coupling modeling unit. The center of mass modeling unit is used to determine the center of mass position of the platform and describe the change of the center of gravity of the platform in combination with the terrain conditions; the leg mechanics unit is used to calculate the reaction force of each leg and its torque balance relationship in different inclination directions of the platform; the leg coupling modeling unit describes the interaction between different legs through a nonlinear coupling relationship to ensure the mechanical balance of the platform under dynamic conditions.

[0063] In this embodiment, the center of mass modeling unit is used to determine the center of gravity position (x c ,y c ,z c), as the core reference data for control system leveling and anti-dumping. The center of mass of the platform will be affected by many factors such as inclination angle and change of gravity direction on different terrains. Therefore, this unit dynamically calculates the actual position of the center of gravity through sensor array data combined with platform structural parameters to achieve real-time update. In general, the change of the center of gravity position is calculated by combining the data of the accelerometer with the structural model of the platform and expressed in three-dimensional coordinate form.

[0064] In this embodiment, the leg mechanics unit is used to analyze the force of each leg and dynamically adjust the reaction force of the leg according to the posture change of the platform. x ) and left and right tilt angles (θ y ) direction satisfies the following equation:

[0065] ∑F i =mg

[0066] Among them, ∑F i is the total reaction force of each leg, m is the total mass of the platform, and g is the acceleration due to gravity. This formula ensures the vertical force balance of the entire platform.

[0067] As an option, the outrigger mechanical unit further establishes the moment balance relationship of the platform in the tilt direction, specifically:

[0068]

[0069] Among them, d i,x and d i,y are the distances between each leg and the center of mass in the front-to-back direction and the left-to-right direction, I x and I y It is the inertia moment of the platform in different directions. This balance relationship provides a reliable theoretical support for the leveling and anti-dumping of the platform.

[0070] In some embodiments, the leg reaction force in the leg mechanics unit is dynamically adjusted by considering the elastic coefficient and damping coefficient of each leg to adapt to the support requirements under different terrain conditions. Assume that the reaction force of each leg is F i ,in:

[0071]

[0072] Among them, k i is the elastic coefficient of the outrigger, indicating the elastic stiffness of the outrigger; c i is the damping coefficient, representing the buffering effect of the outrigger under dynamic stress conditions; z i and are the displacement and velocity of the outriggers, respectively. In practical applications, the magnitude of the outrigger reaction force is adjusted in real time according to the actual position of the center of mass and the relative height difference of each outrigger.

[0073] The outrigger coupling modeling unit is used to describe the nonlinear coupling relationship between the outriggers. Generally, when the platform moves on complex terrain, the forces on each outrigger affect each other. The outrigger coupling modeling unit realizes this characteristic by introducing nonlinear coupling terms.

[0074] As a possible implementation, the dynamic coupling between the legs can be described by the following relationship:

[0075]

[0076] Among them, β x and β y The coupling compensation coefficient is used to control the coupling strength between the front and rear tilt angles and the left and right tilt angles. This coupling relationship automatically produces a compensation effect when the tilt angles in different directions of the platform change, thereby reducing the mutual influence between the tilt angles.

[0077] In some embodiments, the coupling compensation coefficient in the outrigger coupling modeling unit can be dynamically adjusted according to the complexity of the terrain. Specifically, when the platform detects complex terrain such as a slope or uneven ground, the system automatically increases the coupling compensation coefficient to strengthen the interaction between the outriggers, thereby improving the dynamic balance ability of the platform.

[0078] In this embodiment, the dynamic modeling module combines the center of mass modeling, outrigger mechanical analysis and outrigger coupling model to establish a multi-degree-of-freedom dynamic model of the platform, providing a comprehensive and reliable dynamic basis for the subsequent control module. Under the action of the above model, the platform can achieve stable attitude control when driving on complex terrain, and the nonlinear coupling of the outriggers enables the platform to automatically adapt to tilt changes and maintain balance on uneven ground.

[0079] Optimal control module

[0080] The optimal control module calculates the optimal control input of the platform to minimize the leveling error and leg force control error of the platform. In this control system, the attitude perception module and the dynamic modeling module provide the real-time attitude data and mechanical model information of the platform. Based on these data and models, the optimal control module solves the optimal control problem to achieve rapid and accurate adjustment of the platform attitude, so that the platform can maintain a stable state under complex terrain conditions. This module ensures that the control input reaches the optimal state by constructing a weighted objective function and using a numerical iteration method to meet the high-precision requirements of leveling control.

[0081] In this embodiment, the optimal control module includes an objective function unit, an optimal strategy unit and a feedback adjustment unit. The objective function unit defines the objective functions of the leveling error and the outrigger force control error to minimize the overall error; the optimal strategy unit is responsible for calculating the optimal control input based on the objective function; and the feedback adjustment unit is used to dynamically adjust the control input when the posture or external environment changes.

[0082] In general, the objective function unit is used to define the weighted objective function of the platform in leveling control. Specifically, the set objective function J includes both the sum of squares of the leveling error and the sum of squares of the outrigger force control error to ensure that the platform can maintain stability under different terrain conditions. The expression of the objective function is:

[0083]

[0084] in:

[0085] θ x and θ y are the inclination angles of the platform in the front-to-back direction and the left-to-right direction,

[0086] θ d is the target leveling angle (usually 0°),

[0087] F i is the reaction force for each leg, F i,ref is the reference force value for each leg,

[0088] Q x , Q y is the weight coefficient of the leveling error, and R is the weight coefficient of the outrigger force control error.

[0089] In a possible implementation, the objective function unit of the optimal control module can dynamically adjust the weight coefficient Q according to different terrain conditions. x , Q y and R. For example, when the platform is driving on a slope, the weight of the leveling error Q x and Q y It can be appropriately increased to improve the control accuracy of the platform's attitude; on relatively flat terrain, the weight R of the outrigger force control error can be appropriately increased to reduce system power consumption.

[0090] As an option, the optimal strategy unit is used to solve the optimal value of the above objective function. Specifically, to find the control input that minimizes the objective function J, the optimal strategy unit applies the Hamilton-Jacobi-Bellman (HJB) equation, which is used to describe the optimal strategy for state feedback control. The general form of the HJB equation is:

[0091]

[0092] in:

[0093] V(x) represents the value function, which describes the minimum cost of the system from the current state to the target state.

[0094] L(x,u) is the instantaneous cost term, corresponding to the instantaneous error of the platform attitude and outrigger force,

[0095] f(x,u) is the system state equation, which describes the dynamic changes of the platform under different control inputs.

[0096] Since it is difficult to obtain an analytical solution to the HJB equation, in this embodiment, the optimal strategy unit solves the optimal control input u through a numerical iteration method. In the numerical iteration process, the reaction force F of each leg is first calculated. i Initialize and optimize it step by step according to the HJB equation until the objective function J converges to the minimum value. In general, in order to accelerate the iterative convergence speed, the convergence condition can be judged by setting the error threshold. When the iterative error is less than the preset threshold, stop the iteration and output the current optimal control input.

[0097] In some embodiments, in order to adapt to the dynamic changes of the platform, the feedback adjustment unit can dynamically monitor the leveling effect and outrigger force deviation of the platform during the leveling control process. When the system detects that the leveling error or outrigger force control error exceeds the set allowable range, the feedback adjustment unit reactivates the optimal strategy unit and dynamically adjusts the control input u to ensure real-time adjustment of the platform attitude. For example, when the platform is going uphill, due to the large change in the tilt angle, the feedback adjustment unit will dynamically increase the leveling weight coefficient Q x and Q y , and calculates new optimal control inputs in real time, allowing the platform to quickly adapt to terrain changes.

[0098] In another possible implementation, the feedback adjustment unit can also automatically trigger the recalculation of the optimal strategy unit in combination with external disturbances and changes in sensor data to improve the adaptability of the system. For example, when the attitude perception module detects a drastic change in the platform inclination, the feedback adjustment unit will automatically adjust the control parameters and recalculate the outrigger force control input at a higher control frequency, so that the platform always remains stable in a dynamic environment.

[0099] The optimal control module of this embodiment realizes real-time leveling control of the platform under different terrains and disturbance conditions through the coordinated action of the objective function unit, the optimal strategy unit and the feedback adjustment unit.

[0100] Robust Control Module

[0101] The robust control module combines sliding mode control and adaptive gain adjustment methods to dynamically adjust the platform's attitude when the platform encounters external disturbances, terrain changes, or dramatic fluctuations in attitude. The attitude perception module and dynamic modeling module provide real-time attitude information and mechanical data for the robust control module, while the optimal control module provides basic control inputs. The robust control module applies additional anti-disturbance control on this basis to ensure the stability of the platform in complex environments.

[0102] In this embodiment, the robust control module specifically includes a sliding mode control unit, an adaptive gain unit, and a coupling compensation unit. The sliding mode control unit is used to define the sliding mode surface of the platform in the front-to-back direction and the left-to-right direction, and realizes rapid attitude leveling through the sliding mode control law; the adaptive gain unit dynamically adjusts the sliding mode control gain according to the change of the platform attitude to improve the adaptability of the system; the coupling compensation unit is used to reduce the dynamic coupling effect between the front-to-back direction and the left-to-right direction, thereby improving the accuracy of attitude control.

[0103] In general, the sliding mode control unit establishes the anti-disturbance mechanism of the control system by defining the sliding mode surface. Specifically, the fore-aft inclination error (θ x -θ d ) and left and right tilt angle errors (θ y -θ d ) constitutes the basic input of sliding mode control, let s x and y Represent the inclination errors in the front-to-back direction and the left-to-right direction respectively, then the sliding surface S x and S y Defined as:

[0104]

[0105]

[0106] Among them, λ x and λ y To adjust the parameters, it is usually used to control the response speed and convergence characteristics of the system. In one possible implementation, the control law on the sliding surface calculates the control input according to the real-time inclination change of the platform. To achieve the stability of the platform on the sliding surface, the sliding mode control law is defined as:

[0107] u x =-η x ·sgn(S x )-k x ·S x

[0108] u y =-η y ·sgn(S y)-k y ·S y

[0109] Among them, η x and η y is the gain coefficient of the nonlinear term, which is used to compensate for the uncertainty and external disturbance in the system; k x and k y is the sliding mode gain, which controls the convergence speed of the control system on the sliding mode surface. x and S y The sign function is adjusted so that the system can generate corresponding control inputs under different posture deviation conditions to ensure that the platform remains stable within the sliding surface.

[0110] As an option, the adaptive gain unit automatically adjusts the sliding mode control gain according to the current attitude deviation to enhance the robustness of the system. Specifically, the adaptive gain is adjusted based on the real-time inclination error and rate of change of the platform. For example, when the platform inclination changes greatly or the terrain fluctuates violently, the adaptive gain unit will automatically increase the sliding mode gain to improve the response speed of the system. The adaptive gain can be implemented through the following relationship:

[0111] η x (t) = η x,0 +γ x |S x |

[0112] η y (t) = η y,0 +γ y |S y |

[0113] Among them, η x,0 and η y,0 is the initial gain, γ x and γ y The adaptive adjustment coefficient dynamically adjusts the gain according to the deviation on the sliding surface, so that the system can maintain a stable control effect under different terrain conditions. In some embodiments, the adjustment frequency of the adaptive gain unit can be synchronized with the update frequency of the sensor data to ensure the real-time performance of the gain adjustment.

[0114] The coupling compensation unit is used to reduce the dynamic coupling effect of the platform in the front and rear tilt angle and left and right tilt angle directions. Generally, when the platform is driving on complex terrain, the front and rear tilt angle (θ x ) and the left-right inclination angle (θ y ), which is particularly evident on slopes or uneven ground. In order to reduce this coupling effect, the coupling compensation unit introduces a dynamic coupling compensation term C xy, the dynamic coupling is compensated by the product relationship between the front and rear tilt angles and the left and right tilt angles. Specifically, the coupling compensation term is defined as:

[0115]

[0116] Among them, β x and β y is the coupling compensation coefficient, which controls the coupling strength of the front and rear tilt angles and the left and right tilt angles respectively. In one possible implementation, the coupling compensation coefficient can be dynamically adjusted according to the complexity of the terrain. For example, when the platform detects that the terrain is undulating or driving on a slope, the system can increase β x and β y The value of can further reduce the mutual influence between the front and rear tilt angles and the left and right tilt angles, thereby achieving more precise attitude control.

[0117] The robust control module of this embodiment enables the platform to maintain a stable posture under complex terrain and external disturbances through the combined effects of sliding mode control, adaptive gain adjustment and coupling compensation.

[0118] The present invention obtains real-time attitude data through the attitude perception module, and establishes a multi-degree-of-freedom dynamic model of the platform on complex terrain in combination with the dynamic modeling module, providing an accurate mechanical basis for the leveling control of the platform. The optimal control module calculates the optimal control input required for leveling, so that the platform can effectively respond to different terrain changes, while the robust control module uses sliding mode control and adaptive gain adjustment to enhance the system's anti-interference ability when there is external disturbance or drastic change in terrain. The overall system realizes automatic leveling and stability control of the platform in complex and dynamic environments, ensuring safety and operational accuracy during high-altitude operations.

[0119] Please refer to the attached Figure 2 The present invention also provides a control method for a self-propelled insulating lifting platform, comprising the following steps:

[0120] In step S1, the system first obtains the real-time attitude information of the platform, including the front and rear tilt angles, left and right tilt angles and angular velocity of the platform. This step is completed by the attitude perception module, which collects the attitude information of the platform in real time through the multi-axis tilt sensor array to provide the necessary initial data for subsequent modeling and control.

[0121] In step S2, the system establishes a multi-degree-of-freedom dynamic model based on the acquired posture information and the center of gravity position of the platform, combined with the elasticity and damping characteristics of the legs. The dynamic model describes the relationship between the center of gravity position of the platform and the force on the legs, and can dynamically adjust the reaction force of the legs, thereby providing the support mechanics basis of the platform under different terrain conditions.

[0122] In step S3, the system defines a weighted objective function, which includes the leveling error and the outrigger force control error, aiming to minimize the deviation between the platform attitude and the target leveling state. In this step, the system calculates the optimal control input based on the multi-degree-of-freedom model and the objective function to ensure the accuracy and stability of the platform during the leveling process.

[0123] In step S4, the system calculates the control input based on the sliding mode control algorithm, and further enhances the anti-disturbance capability of the system through adaptive gain adjustment and dynamic coupling compensation. This step introduces anti-disturbance terms into the control input, so that the system can make real-time adjustments when there are external disturbances or terrain changes, ensuring the stability of the platform attitude.

[0124] In step S5, the system adjusts the position and reaction force of each leg according to the control input calculated in the previous steps, so that the platform maintains a stable leveling state under different terrain conditions, thereby realizing automatic leveling and anti-dumping functions.

[0125] The method realizes automatic leveling and anti-dumping control of the platform in complex terrain through multi-step coordinated operation.

[0126] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A control system for a self-propelled insulating lifting platform, characterized in that: include: The posture perception module is used to collect the tilt angle and angular velocity of the platform in real time; Dynamic modeling module, used to establish a multi-degree-of-freedom dynamic model of the platform to describe the center of gravity position and outrigger forces of the platform on complex terrain; The optimal control module is used to calculate the optimal control input to minimize the leveling error of the platform; The robust control module, based on the sliding mode control algorithm, realizes the anti-disturbance leveling of the platform under external disturbance conditions.

2. A control system for a self-propelled insulating lifting platform according to claim 1, characterized in that: The posture perception module includes a multi-axis tilt sensor array, which includes a three-axis accelerometer and a three-axis gyroscope, for obtaining the tilt angle and angular velocity information of the platform in the front-back direction and the left-right direction, and fusing the data through a weighted average method.

3. The control system of a self-propelled insulating lifting platform according to claim 1 is characterized in that: The dynamic modeling module is used to construct a nonlinear multi-degree-of-freedom dynamic model, including: A center of mass modeling unit is used to determine the three-dimensional position of the center of gravity of the platform to describe the distribution of the center of gravity of the platform on uneven ground; The outrigger mechanics unit is used to calculate the reaction force of each outrigger so that the platform can maintain dynamic balance in the forward and backward tilt and left and right tilt directions; The coupling modeling unit between the legs is used to calculate the interaction force between the legs to adapt to complex terrain.

4. A control system for a self-propelled insulating lifting platform according to claim 3, characterized in that: The outrigger mechanics unit determines the reaction force of the outrigger according to the elastic coefficient and damping coefficient of each outrigger to ensure that the outrigger can adjust the platform posture when subjected to force.

5. The control system of a self-propelled insulating lifting platform according to claim 3, characterized in that: The dynamic modeling module establishes a nonlinear equilibrium relationship of the outrigger forces according to the following conditions: At different tilt angles of the platform, the reaction force of the outriggers is proportional to the moment of inertia of the platform to maintain the stability of the platform in the forward and backward tilt and left and right tilt directions.

6. The control system of a self-propelled insulating lifting platform according to claim 1, characterized in that: The optimal control module comprises: An objective function unit, used for defining a weighted objective function of a leveling error and an outrigger force control error, so as to minimize the leveling error of the platform in a front-to-back direction and a left-to-right direction; The optimal strategy unit solves the optimal value of the objective function through a numerical iteration method and is used to output the optimal control input of the platform legs.

7. A control system for a self-propelled insulating lifting platform according to claim 6, characterized in that: The objective function defined by the objective function unit includes the leveling error and the square sum of the outrigger contact force error, and the objective function is used to minimize the leveling error of the platform under complex terrain conditions.

8. The control system of a self-propelled insulating lifting platform according to claim 1, characterized in that: The robust control module comprises: The sliding mode control unit is used to define the sliding mode surface of the platform in the forward and backward tilting and left and right tilting directions, and realize the rapid leveling of the platform through the sliding mode control law; Adaptive gain unit, used to automatically adjust the sliding mode control gain according to the change of platform inclination error to enhance the anti-disturbance performance of the system; The coupling compensation unit is used to reduce the dynamic coupling effect in the front-to-back tilt and left-to-right tilt directions.

9. A control system for a self-propelled insulating lifting platform according to claim 8, characterized in that: The sliding mode control unit adjusts the sliding mode surface response speed through a nonlinear gain, and the gain adjustment parameters include: The adaptive gain calculated based on the current posture of the platform and external disturbance conditions enables the system to maintain rapid response capabilities in dynamic environments.

10. A control method for a self-propelled insulating lifting platform, based on the system according to any one of claims 1 to 9, characterized in that: The following steps are involved: Obtain the real-time attitude information of the platform, and obtain the front and rear tilt angles, left and right tilt angles, and angular velocity of the platform; A multi-degree-of-freedom dynamic model is established based on the center of gravity position of the platform and the force on the outriggers, and the reaction force of each outrigger is determined by the elasticity and damping coefficient of the outriggers; Define a weighted objective function, including the leveling error and the outrigger force control error, and solve the optimal control input according to the objective function; The control input is calculated based on the sliding mode control algorithm, and the platform's anti-disturbance is achieved through adaptive gain adjustment and dynamic coupling compensation; Based on the calculated control input, the platform outrigger position is adjusted to keep the platform in a stable leveled state on complex terrain.

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