Multi-axis motion control method and system for automation equipment

Abstract

The invention discloses a multi-axis motion control method and system for automation equipment, relates to the technical field of multi-axis motion control, and designs and adjusts an adaptive compensation strategy based on real-time errors and equipment states by collecting data of the equipment in real time. The self-adaptive capability enables the system to flexibly cope with factors such as aging of equipment and external environment change, and ensures that high control precision and stability are always kept under different working conditions. Through cooperation of the data acquisition and processing module and the error detection and analysis module, the system can accurately obtain a motion error value and a change trend. Therefore, an accurate basis is provided for subsequent compensation adjustment, the compensation amount can be dynamically optimized in each control period, error accumulation is avoided, and the system precision and stability are improved; by cleaning and standardizing the multi-axis data set DW, the system can identify and evaluate the source of the error more accurately, so that a more refined compensation strategy is designed.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-axis motion control, and in particular to a multi-axis motion control method and system for automation equipment. Background Art

[0002] The multi-axis motion control system of automation equipment belongs to the field of automation control and is an important part of modern industrial automation technology. Automation control systems are widely used in industrial production, machinery manufacturing, robotics, precision instruments and other fields, promoting the improvement of production efficiency and product quality. Especially in production lines with high precision and high efficiency requirements, motion control systems play a core role. In the specific application of automation control systems, multi-axis motion control systems are particularly important. They coordinate multiple actuators to work together to accurately control the motion path and state of the equipment. They are widely used in CNC machine tools, robots, automated assembly lines and other scenarios.

[0003] Existing control systems usually rely on fixed compensation parameters and control strategies. Although this traditional approach can meet some basic control needs, in actual applications, as the equipment is used for a longer time, the working state of the equipment will change, resulting in a gradual decrease in the control accuracy of the system. In addition, traditional control systems have poor ability to cope with changes in the external environment and lack sufficient flexibility and adaptability.

[0004] The shortcomings of the current control system mainly stem from its lack of adaptive capabilities for dynamic changes in equipment. Fixed compensation parameters fail to take into account the impact of external factors such as equipment wear and temperature changes in real time, making it impossible to adjust the control strategy in time to cope with these changes. This results in the system being unable to effectively cope with the accumulation of errors caused by equipment aging, environmental changes, etc. As the equipment is used for a longer time, the control accuracy gradually decreases, which may be manifested as increased repeatability errors on the production line and increased motion trajectory deviations, ultimately affecting product accuracy and production efficiency. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a multi-axis motion control method and system for automated equipment, which solves the problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a multi-axis motion control system for automation equipment, including a data acquisition and processing module, an error detection and analysis module, an adaptive controller design module, a compensation adjustment and motion control module, a feedback and state update module and a performance evaluation and optimization module; The data acquisition and processing module collects data from the multi-axis control system through sensors, fits it into an original data group AW, and performs preprocessing to obtain a multi-axis data group DW; The error detection and analysis module performs real-time error detection based on the acquired multi-axis data set DW, and obtains the error value Ex and the error change trend Etr; The adaptive controller design module designs an adaptive controller to generate a compensation strategy based on the obtained error value Ex and error change trend Etr, obtains the response compensation amount Udy, and calculates the final compensation amount Ux(t); The compensation adjustment and motion control module adjusts the motion trajectory, bearing speed Vx and bearing acceleration ax of each bearing according to the final compensation amount Ux(t) obtained, performs real-time compensation, and feeds back to the compensation strategy; After the real-time compensation is completed, the feedback and status update module collects the device feedback data, readjusts the compensation strategy, and obtains the new compensation amount nUx; The performance evaluation and optimization module evaluates the overall performance of the system based on the error value Ex, the new compensation amount nUx and the error change trend Etr, obtains the system performance score PF, and adjusts the control strategy to obtain the adjusted compensation amount TnUx.

[0007] Preferably, the data acquisition and processing module includes a data acquisition unit and a data preprocessing unit; The data acquisition unit collects the bearing data through sensors, including bearing temperature Ta, bearing acceleration ax, bearing load La and motion deviation Px, and fits them into the original data group AW; Among them, the bearing temperature Ta is acquired through the temperature sensor, which can detect the temperature changes caused by friction and load factors during the operation of the equipment; The bearing acceleration ax is acquired through the acceleration sensor; The bearing load La is acquired through the load sensor, and the bearing load La reflects the working status of each axis; The motion deviation Px is acquired through the position sensor, reflecting the difference between the actual position Xact of the bearing and the target position Xtar; The motion deviation Px is obtained by the following formula: ; The data preprocessing unit cleans and standardizes the acquired raw data set AW to obtain a multi-axis data set DW; Cleaning includes filtering and outlier processing. The filtering process removes noise and interference in the original data set AW by using a filter; the outlier processing removes outliers in the original data set AW by using an outlier detection algorithm. Standardization processing uses standardization methods to convert data into a uniform scale to obtain a multi-axis data set DW; The multi-axis data set DW is obtained by the following formula: ; Wherein, DWb represents the b-th data item in the multi-axis data group DW, AWb represents the b-th data item in the original data group AW, μAWb represents the mean of the b-th data item in the original data group AW, and σAWb represents the standard deviation of the b-th data item in the original data group AW.

[0008] Preferably, the error detection and analysis module includes a data feature extraction unit and an error acquisition unit: The data feature extraction unit extracts features from the multi-axis data set DW, extracts features that affect motion accuracy and control effect, including temperature change rate ΔTa, load change rate ΔLa and motion deviation change rate ΔPx, and fits them into a change feature set LP; The temperature change rate ΔTa is obtained by the following formula: ; Where, Ta(t) represents the bearing temperature at time t, Ta(t-1) represents the bearing temperature at time t-1, and Δt represents the time interval; The load change rate ΔLa is obtained by the following formula: ; Where, La(t) represents the bearing load at time t, and La(t-1) represents the bearing load at time t-1; The motion deviation change rate ΔPx is obtained by the following formula: ; Where, Px(t) represents the motion deviation at time t, and Px(t-1) represents the motion deviation at time t-1; The error acquisition unit calculates the error value Ex based on the acquired temperature change rate ΔTa, load change rate ΔLa and motion deviation change rate ΔPx, and dynamically analyzes the error value Ex, smoothes the error curve through time series analysis, and identifies the error change trend Etr; this analysis helps determine whether the error is caused by instantaneous disturbance or long-term change; The error value Ex is obtained by the following formula: ; ; In the formula, represent the preset weight values ​​of the temperature change rate ΔTa, the load change rate ΔLa and the motion deviation change rate ΔPx, respectively, and , fin represents the interaction function between features, Represents the interaction coefficient of the temperature change rate ΔTa and the load change rate ΔLa, Represents the interaction coefficient of the load change rate ΔLa and the motion deviation change rate ΔPx, Represents the interaction coefficient between the temperature change rate ΔTa and the motion deviation change rate ΔPx; represents the coupling effect between different features; The error change trend Etr is obtained by the following formula: ; Where Ex(ti) represents the error value at time ti, n represents the time window size for calculating the error trend, and i represents the index variable used to traverse the past n time points.

[0009] Preferably, the adaptive controller design module includes an error response design unit and a dynamic compensation adjustment unit; The error response design unit designs the error response function based on the obtained error value Ex and error change trend Etr, combined with PID control, to obtain the error compensation amount Uex(t); The error compensation amount Uex (t) is obtained by the following formula: ; In the formula, Ex represents the error value at time t, Kp represents the proportional gain, Ki represents the integral gain, Kd represents the differential gain, dt represents the integral, represents the rate of change of error at time t; The error compensation amount Uex(t) obtained is combined with the error change trend Etr, and the error change trend Etr is used as a dynamic weight adjustment compensation strategy to obtain the response compensation amount Udy; Among them, the error change trend Etr can affect the amplitude of the compensation response; When the error value Ex continues to increase within a fixed period, the controller needs to increase its response; When the error value Ex remains stable within a fixed period, the controller reduces the response; The response compensation amount Udy is obtained by the following formula: ; Where fq represents the trend change function.

[0010] Preferably, the dynamic compensation adjustment unit obtains the final compensation amount Ux(t) based on the obtained response compensation amount Udy, combined with the temperature change rate ΔTa and the load change rate ΔLa; The temperature compensation value Uta is obtained by the influence of the temperature change rate ΔTa on the bearing motion performance; The temperature compensation value Uta is obtained by the following formula: ; In the formula, Indicates the sensitivity coefficient of temperature change to the compensation amount; Obtain the load compensation amount Ula through the influence of the load change rate ΔLa on the bearing stability and motion accuracy; The load compensation amount Ula is obtained by the following formula: ; In the formula, Indicates the influence coefficient of load change on compensation amount; Combine the temperature compensation Uta and the load compensation Ula to obtain the final compensation Ux (t); The final compensation amount Ux(t) is obtained by the following formula: ; Where k1 and k2 represent adjustment coefficients.

[0011] Preferably, the compensation adjustment and motion control module includes a motion trajectory correction unit and a speed and acceleration adjustment unit; The motion trajectory correction unit adjusts and corrects the motion trajectory of the bearing in real time according to the final compensation amount Ux(t) obtained, and corrects the deviation on the trajectory through the compensation amount, so that the equipment can accurately run along the predetermined path and obtain the position Xz of the bearing; Through coordination with the motion paths of other axes in the system, the correction path is adjusted based on feedback from the actual deviation of each axis. After each correction, the new path will be fed back to the next control cycle. If the system path correction effect is not ideal, the final compensation amount Ux (t) will be adjusted again to ensure that the final path is as accurate as possible. The control system adjusts the compensation strategy based on feedback to ensure the continuity and stability of the path correction process. The position Xz of the bearing is obtained by the following formula: ; Where, Xz(t) represents the position of the bearing at time t, and Xz(t-1) represents the position of the bearing at time t-1; The speed and acceleration adjustment unit adjusts the bearing speed Vx and the bearing acceleration ax in real time according to the corrected bearing position Xz; The bearing speed Vx is obtained by the following formula: ; Where Vx(t) represents the bearing speed at time t; The bearing acceleration ax is obtained by the following formula: ; Where ax(t) represents the bearing acceleration at time t; According to the real-time feedback of the bearing speed Vx and the bearing acceleration ax, the compensation strategy is dynamically adjusted to regulate the changes of the bearing speed Vx and the bearing acceleration ax to maintain the normal state of the bearing within a fixed period.

[0012] Preferably, the feedback and status update module includes a device status collection and analysis unit and a compensation strategy adjustment and update unit; The equipment status collection and analysis unit collects the feedback data of the bearing in real time through sensors, including the new motion deviation nPx and the new bearing acceleration nax, processes and evaluates the collected new motion deviation nPx and the new bearing acceleration nax, analyzes the deviation between the motion accuracy and acceleration of the bearing and the target position, obtains the state error index ESt, and compares it with the preset error threshold Tes to determine the compensation state of the bearing; The state error index ESt is obtained by the following formula: ; The compensation status of the bearing is obtained by matching: When the state error index ESt ≤ the error threshold Tes, it means that the bearing is in normal condition and no compensation is required; When the state error index ESt>error threshold Tes, it means that the bearing state is abnormal and compensation is required.

[0013] Preferably, the compensation strategy adjustment and update unit readjusts the compensation strategy according to the acquired state error index ESt; by dynamically adjusting the compensation amount, it is ensured that the device always maintains the best accuracy and stability during the entire operation process; When the state error index ESt>error threshold Tes, based on the state error index ESt of the bearing state evaluation result, the final compensation amount Ux(t) is re-evaluated and adjusted accordingly to obtain a new compensation amount nUx; The new compensation value nUx is obtained by the following formula: ; Where Kn represents the adjustment factor of the compensation amount.

[0014] Preferably, the performance evaluation and optimization module evaluates the overall performance of the system based on the error value Ex, the new compensation amount nUx and the error change trend Etr, obtains the system performance score PF, and compares it with the preset performance score threshold Tpf to determine the effectiveness of the current control strategy; The system performance score PF is obtained by the following formula: ; Where Tp represents the evaluation period, represent the preset weight values ​​of the error value Ex, the new compensation amount nUx and the error change trend Etr respectively, and ; The effectiveness of the control strategy is obtained by matching: When the system performance score PF ≥ the performance score threshold Tpf, it means that the control strategy has met the requirements and does not need to be adjusted; When the system performance score PF is less than the performance score threshold Tpf, it means that the control strategy does not meet the requirements and needs to be adjusted to adjust the new compensation amount nUx and obtain the adjusted compensation amount TnUx; The adjusted compensation amount TnUx is obtained by the following formula: ; In the formula, C represents the compensation factor, which controls the adjustment amplitude of the compensation amount.

[0015] Based on the adjusted control strategy, the system will update the compensation amount and enter the next control cycle; this enables the system to continuously adjust and optimize the control strategy based on real-time evaluation results.

[0016] A multi-axis motion control method for automation equipment comprises the following steps: Step 1: The data acquisition and processing module collects data in the multi-axis control system through sensors, fits it into an original data group AW, and performs preprocessing to obtain a multi-axis data group DW; Step 2: The error detection and analysis module performs real-time error detection based on the acquired multi-axis data set DW to obtain the error value Ex and the error change trend Etr; Step 3: The adaptive controller design module designs an adaptive controller to generate a compensation strategy based on the obtained error value Ex and error change trend Etr, obtains the response compensation amount Udy, and calculates the final compensation amount Ux(t); Step 4: The compensation adjustment and motion control module adjusts the motion trajectory, bearing speed Vx and bearing acceleration ax of each bearing according to the final compensation amount Ux(t) obtained, performs real-time compensation, and feeds back to the compensation strategy; Step 5: After the real-time compensation is completed, the feedback and status update module collects the device feedback data, readjusts the compensation strategy, and obtains the new compensation amount nUx; Step 6: The performance evaluation and optimization module evaluates the overall performance of the system based on the error value Ex, the new compensation amount nUx and the error change trend Etr, obtains the system performance score PF, and adjusts the control strategy to obtain the adjusted compensation amount TnUx.

[0017] The present invention provides a multi-axis motion control method and system for automation equipment, which has the following beneficial effects: (1) When the system is running, the adaptive compensation strategy is designed and adjusted based on the real-time error and equipment status by collecting data from the equipment in real time. This adaptive capability enables the system to flexibly respond to factors such as equipment aging and changes in the external environment, ensuring that high control accuracy and stability are always maintained under different working conditions. Through the cooperation of the data acquisition and processing module and the error detection and analysis module, the system can monitor and analyze the motion state of the equipment in real time, and accurately obtain the motion error value and change trend. This provides an accurate basis for subsequent compensation adjustments, so that the compensation amount can be dynamically optimized within each control cycle, avoiding error accumulation and improving system accuracy and stability.

[0018] The adaptive controller design module generates compensation strategies based on real-time errors and change trends, and incorporates temperature changes and load changes into the compensation adjustment process. This compensation adjustment method based on dynamic changes can better cope with the impact of external factors such as equipment aging and temperature fluctuations on system accuracy, effectively reduce errors, and improve production efficiency and product quality.

[0019] (2) The data preprocessing unit cleans and standardizes the original data set AW, removes noise and interference, and makes data of different dimensions comparable. Through filtering and outlier detection, the system can ensure the high quality and accuracy of the data and reduce errors caused by noise or outliers. Standardization enables sensor data from different sources to be scaled to improve the accuracy and effectiveness of subsequent analysis and control strategy design. In multi-axis motion control systems, accurate error detection is the key to ensuring high-precision operation of equipment. By cleaning and standardizing the multi-axis data set DW, the system can more accurately identify and evaluate the source of the error, thereby designing a more refined compensation strategy.

[0020] (3) The combination of the error response design unit and the dynamic compensation adjustment unit enables the control system to adjust the compensation strategy based on the error change trend. When the error value continues to increase within a fixed period, the controller will increase the response to eliminate the deviation; when the error is stable, the system will reduce the response to avoid overcompensation. This trend-based dynamic compensation method can optimize the control process, avoid overreaction and system oscillation, and thus improve the stability and response efficiency of the control system.

[0021] Not only the error value and change trend are taken into account, but also the temperature change rate ΔTa and load change rate ΔLa are included in the compensation adjustment process. This enables the compensation strategy to be adjusted in real time according to changes in the environment in which the equipment is operating. For example, temperature fluctuations may affect the motion performance of the equipment, while load changes will affect motion accuracy and stability. In this way, the system can adapt to changes in the working environment more accurately, ensuring that the equipment can maintain high-precision control under different working conditions.

[0022] (4) The motion trajectory of the bearing is adjusted in real time according to the compensation amount Ux(t) through the motion trajectory correction unit. This trajectory correction based on real-time compensation ensures that the equipment can always move accurately along the predetermined path during operation, avoiding trajectory deviations caused by changes in the external environment or fluctuations in equipment status. Compared with the traditional control system that relies on fixed trajectory planning, this adaptive correction method can better cope with dynamic changes in equipment and improve the accuracy and flexibility of the system. The speed and acceleration adjustment unit dynamically adjusts the speed and acceleration of the bearing according to the corrected bearing position Xz. This enables the system to optimize the operating state of the bearing based on real-time feedback, avoiding the loss of accuracy caused by unstable motion or uneven speed in traditional control systems. Through continuous speed and acceleration adjustment, the system can maintain the normal state of the bearing within a fixed period, ensuring efficient operation and precision control of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic diagram of a multi-axis motion control system for automation equipment according to the present invention; Figure 2 A schematic diagram of the steps of a multi-axis motion control method for automation equipment according to the present invention; Figure 3 A schematic diagram of the system block diagram flow chart of the compensation acquisition of the present invention; Figure 4 A line graph obtained for the error value of the present invention; Figure 5 It is a bar graph of the final compensation amount of the present invention. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0025] Example 1 The present invention provides a multi-axis motion control system for automation equipment. Figures 1 to 5 , including data acquisition and processing module, error detection and analysis module, adaptive controller design module, compensation adjustment and motion control module, feedback and state update module and performance evaluation and optimization module; The data acquisition and processing module collects data from the multi-axis control system through sensors, fits it into an original data group AW, and performs preprocessing to obtain a multi-axis data group DW; The error detection and analysis module performs real-time error detection based on the acquired multi-axis data set DW, and obtains the error value Ex and the error change trend Etr; The adaptive controller design module designs an adaptive controller to generate a compensation strategy based on the obtained error value Ex and error change trend Etr, obtains the response compensation amount Udy, and calculates the final compensation amount Ux(t); The compensation adjustment and motion control module adjusts the motion trajectory, bearing speed Vx and bearing acceleration ax of each bearing according to the final compensation amount Ux(t) obtained, performs real-time compensation, and feeds back to the compensation strategy; After the real-time compensation is completed, the feedback and status update module collects the device feedback data, readjusts the compensation strategy, and obtains the new compensation amount nUx; The performance evaluation and optimization module evaluates the overall performance of the system based on the error value Ex, the new compensation amount nUx and the error change trend Etr, obtains the system performance score PF, and adjusts the control strategy to obtain the adjusted compensation amount TnUx.

[0026] In this embodiment, the adaptive compensation strategy is designed and adjusted based on the real-time error and device status by collecting the multi-axis data of the device in real time. This adaptive capability enables the system to flexibly respond to factors such as the aging of the equipment and changes in the external environment, ensuring that high control accuracy and stability are always maintained under different working conditions. Through the cooperation of the data acquisition and processing module and the error detection and analysis module, the system can monitor and analyze the motion state of the device in real time, and accurately obtain the motion error value and change trend. This provides an accurate basis for subsequent compensation adjustments, so that the compensation amount can be dynamically optimized in each control cycle, avoiding error accumulation and improving system accuracy and stability.

[0027] The adaptive controller design module generates compensation strategies based on real-time errors and change trends, and incorporates temperature changes and load changes into the compensation adjustment process. This compensation adjustment method based on dynamic changes can better cope with the impact of external factors such as equipment aging and temperature fluctuations on system accuracy, effectively reduce errors, and improve production efficiency and product quality.

[0028] The feedback and status update module can collect feedback data from the equipment after the compensation is completed, and readjust the compensation strategy based on the real-time feedback. This real-time feedback mechanism enables the system to continuously optimize itself throughout the operation process and promptly correct possible control deviations, thereby avoiding the loss of accuracy caused by inflexible parameters in traditional systems. The performance evaluation and optimization module can comprehensively consider the error value, new compensation amount, and error change trend, evaluate the overall system performance, and optimize the control strategy. By evaluating and adjusting the control strategy in real time, the system can continuously maintain optimal performance, thereby avoiding performance degradation caused by the control strategy not adapting to system changes.

[0029] Example 2 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the data acquisition and processing module includes a data acquisition unit and a data pre-processing unit; The data acquisition unit collects the bearing data through sensors, including bearing temperature Ta, bearing acceleration ax, bearing load La and motion deviation Px, and fits them into the original data group AW; Among them, the bearing temperature Ta is acquired through the temperature sensor, which can detect the temperature changes caused by friction and load factors during the operation of the equipment; The bearing acceleration ax is acquired through the acceleration sensor; The bearing load La is acquired through the load sensor, and the bearing load La reflects the working status of each axis; The motion deviation Px is acquired through the position sensor, reflecting the difference between the actual position Xact of the bearing and the target position Xtar; The motion deviation Px is obtained by the following formula: ; The data preprocessing unit cleans and standardizes the acquired raw data set AW to obtain a multi-axis data set DW; Cleaning includes filtering and outlier processing. The filtering process removes noise and interference in the original data set AW by using a filter; the outlier processing removes outliers in the original data set AW by using an outlier detection algorithm. Standardization processing uses standardization methods to convert data into a uniform scale to obtain a multi-axis data set DW; The multi-axis data set DW is obtained by the following formula: ; Wherein, DWb represents the b-th data item in the multi-axis data group DW, AWb represents the b-th data item in the original data group AW, μAWb represents the mean of the b-th data item in the original data group AW, and σAWb represents the standard deviation of the b-th data item in the original data group AW.

[0030] In this embodiment, multiple sensors are integrated to collect data in real time. This comprehensive real-time data collection capability enables the control system to understand the operating status of the equipment in detail and promptly detect and respond to any abnormalities in the operation of the equipment. Compared with traditional control systems, this can provide more accurate monitoring and control and enhance the reliability of the system. The data acquisition unit generates a raw data set AW by integrating the data from different sensors. These data cover multiple aspects of the operation of the equipment. By fusing and analyzing data from multiple dimensions, the system can more comprehensively and accurately identify the status and potential problems of the equipment.

[0031] The data preprocessing unit cleans and standardizes the raw data set AW, removes noise and interference, and makes data of different dimensions comparable. Through filtering and outlier detection, the system can ensure the high quality and accuracy of data and reduce errors caused by noise or outliers. Standardization allows sensor data from different sources to be scaled uniformly, thereby improving the accuracy and effectiveness of subsequent analysis and control strategy design.

[0032] In multi-axis motion control systems, accurate error detection is the key to ensuring high-precision operation of equipment. By cleaning and standardizing the multi-axis data set DW, the system can more accurately identify and evaluate the source of the error, thereby designing a more refined compensation strategy. This enables the system to dynamically adjust the compensation strategy, compensate for errors caused by equipment aging, external environment, etc. in real time, and improve control accuracy. By optimizing the data collection and processing process, the system can process large amounts of real-time data more efficiently and reduce control errors caused by poor data quality. This not only improves the reliability of the system, but also reduces production downtime caused by equipment errors and inaccurate control, thereby improving production efficiency.

[0033] Example 3 This embodiment is explained in Example 2. Please refer to Figure 3 and Figure 4 , specifically: the error detection and analysis module includes a data feature extraction unit and an error acquisition unit: The data feature extraction unit extracts features from the multi-axis data set DW, extracts features that affect motion accuracy and control effect, including temperature change rate ΔTa, load change rate ΔLa and motion deviation change rate ΔPx, and fits them into a change feature set LP; The temperature change rate ΔTa is obtained by the following formula: ; Where, Ta(t) represents the bearing temperature at time t, Ta(t-1) represents the bearing temperature at time t-1, and Δt represents the time interval; The load change rate ΔLa is obtained by the following formula: ; Where, La(t) represents the bearing load at time t, and La(t-1) represents the bearing load at time t-1; The motion deviation change rate ΔPx is obtained by the following formula: ; Where, Px(t) represents the motion deviation at time t, and Px(t-1) represents the motion deviation at time t-1; The error acquisition unit calculates and acquires the error value Ex according to the acquired temperature change rate ΔTa, load change rate ΔLa and motion deviation change rate ΔPx, and dynamically analyzes the error value Ex, smoothes the error curve through time series analysis, and identifies the error change trend Etr; The error value Ex is obtained by the following formula, as shown in Table 1: ; ; In the formula, represent the preset weight values ​​of the temperature change rate ΔTa, the load change rate ΔLa and the motion deviation change rate ΔPx, respectively, and , fin represents the interaction function between features, Represents the interaction coefficient of the temperature change rate ΔTa and the load change rate ΔLa, Represents the interaction coefficient of the load change rate ΔLa and the motion deviation change rate ΔPx, Represents the interaction coefficient between the temperature change rate ΔTa and the motion deviation change rate ΔPx; Specific example: set up They are 0.4, 0.35 and 0.25 respectively; Get the temperature change rate ΔTa=0.20; Load change rate ΔLa=0.50; Motion deviation change rate ΔPx=0.05; fin(LP) = 0.038; Calculate and obtain the error value Ex; ; Table 1 Error value calculation acquisition table; The error change trend Etr is obtained by the following formula: ; Where Ex(ti) represents the error value at time ti, n represents the time window size for calculating the error trend, and i represents the index variable used to traverse the past n time points.

[0034] In this embodiment, the data feature extraction unit can comprehensively analyze the factors that affect the motion accuracy and control effect of the equipment by extracting multiple features. By extracting and fitting these change features, the system can accurately identify and evaluate the changes in the equipment state, thereby effectively locating the error source. This comprehensive feature extraction enhances the system's ability to respond to complex factors and can accurately capture subtle changes in the equipment under dynamic working conditions.

[0035] The error acquisition unit calculates the temperature change rate, load change rate, and motion deviation change rate, and can evaluate the motion error of the device in real time. These calculation results are combined with the dynamic analysis method to smooth the error curve and identify the error change trend. This dynamic analysis method can help the system identify long-standing errors and sudden error changes in a timely manner, so as to take appropriate compensation measures.

[0036] This embodiment calculates the error value by assigning weights to different features and combining their interaction effects. This multi-feature joint optimization method can comprehensively consider the impact of multiple factors on motion accuracy and control effect, and can achieve more accurate error identification and correction compared to the error detection of a single feature. By assigning appropriate weights to each feature, the system can more reasonably adjust the compensation strategy according to the actual operating conditions and optimize the overall performance of the equipment. The calculation of the error change trend Etr provides the system with a long-term error evaluation and prediction mechanism. By smoothing the historical error data, the system can accurately identify the long-term trend of the error, which helps to avoid unnecessary control adjustments due to short-term error fluctuations. The identification of error trends allows the compensation strategy to be adjusted more specifically, avoiding overcompensation or delayed response, and ensuring that the equipment always remains in the best operating state.

[0037] By integrating multi-dimensional real-time data acquisition, feature extraction, error detection and dynamic analysis, this embodiment can effectively respond to changes in equipment in different working environments and improve the robustness of the system; through more accurate error detection and dynamic compensation strategies, the system can adjust the motion trajectory and control parameters in real time to reduce the error accumulation caused by equipment aging or changes in the external environment. Accurate control not only improves the motion accuracy of the equipment, but also reduces downtime and the production of substandard products caused by errors, thereby improving production efficiency and product quality.

[0038] Example 4 This embodiment is explained in Example 3, please refer to Figure 3 and Figure 5,Specifically: the adaptive controller design module includes an error response ,design unit and a dynamic compensation adjustment unit; The error response design unit designs the error response function based on the obtained error value Ex and error change trend Etr, combined with PID control, to obtain the error compensation amount Uex(t); The error compensation amount Uex (t) is obtained by the following formula: ; In the formula, Ex represents the error value at time t, Kp represents the proportional gain, Ki represents the integral gain, Kd represents the differential gain, dt represents the integral, represents the rate of change of error at time t; The error compensation amount Uex(t) obtained is combined with the error change trend Etr, and the error change trend Etr is used as a dynamic weight adjustment compensation strategy to obtain the response compensation amount Udy; Among them, the error change trend Etr can affect the amplitude of the compensation response; When the error value Ex continues to increase within a fixed period, the controller needs to increase its response; When the error value Ex remains stable within a fixed period, the controller reduces the response; The response compensation amount Udy is obtained by the following formula: ; Where fq represents the trend change function.

[0039] The dynamic compensation adjustment unit obtains the final compensation amount Ux(t) based on the obtained response compensation amount Udy, combined with the temperature change rate ΔTa and the load change rate ΔLa; The temperature compensation value Uta is obtained by the influence of the temperature change rate ΔTa on the bearing motion performance; The temperature compensation value Uta is obtained by the following formula: ; In the formula, Indicates the sensitivity coefficient of temperature change to the compensation amount; Obtain the load compensation amount Ula through the influence of the load change rate ΔLa on the bearing stability and motion accuracy; The load compensation amount Ula is obtained by the following formula: ; In the formula, Indicates the influence coefficient of load change on compensation amount; Combine the temperature compensation Uta and the load compensation Ula to obtain the final compensation Ux (t); The final compensation amount Ux(t) is obtained by the following formula: ; Where k1 and k2 represent adjustment coefficients.

[0040] Table 2 Final compensation calculation table: In this embodiment, an adaptive control algorithm based on the error value Ex and the error change trend Etr is introduced, and the error response function is designed by combining PID control. Compared with the traditional fixed compensation method, this adaptive response mechanism can adjust the compensation amount in real time and flexibly compensate according to the actual state of the equipment. This dynamic adjustment based on the error change trend improves the flexibility of the system, enabling it to respond to the increase or decrease of the error in a timely manner and maintain the stability and accuracy of the system.

[0041] The combination of the error response design unit and the dynamic compensation adjustment unit enables the control system to adjust the compensation strategy based on the error change trend. When the error value continues to increase within a fixed period, the controller will increase the response to eliminate the deviation; when the error is stable, the system will reduce the response to avoid overcompensation. This trend-based dynamic compensation method can optimize the control process, avoid overreaction and system oscillation, and thus improve the stability and response efficiency of the control system.

[0042] Not only the error value and change trend are taken into account, but also the temperature change rate ΔTa and load change rate ΔLa are included in the compensation adjustment process. This enables the compensation strategy to be adjusted in real time according to changes in the environment in which the equipment is operating. For example, temperature fluctuations may affect the motion performance of the equipment, while load changes will affect motion accuracy and stability. In this way, the system can adapt to changes in the working environment more accurately, ensuring that the equipment can maintain high-precision control under different working conditions.

[0043] The dynamic adjustment of temperature compensation Uta and load compensation Ula ensures that the control strategy can adapt to the operating status of the equipment in real time. By adjusting the sensitivity and influence coefficient of temperature change and load change, the system can effectively deal with the impact of external environmental fluctuations on the motion accuracy of the equipment. This mechanism improves the system's adaptability to dynamic environmental changes, reduces errors caused by external factors, and thus improves the stability of the system.

[0044] The final compensation amount Ux(t) combines factors such as error response, temperature change, and load change to ensure that the compensation amount in each control cycle can be dynamically adjusted to minimize motion errors and optimize control accuracy. This flexible and intelligent compensation strategy effectively avoids the problem of reduced control accuracy caused by fixed compensation in traditional methods and improves the stability of the system in long-term operation.

[0045] Example 5 This embodiment is explained in Example 4. Please refer to Figure 1 ,Specifically: the compensation adjustment and motion control module includes a motion trajectory correction unit and a speed and acceleration adjustment unit; The motion trajectory correction unit adjusts and corrects the motion trajectory of the bearing in real time according to the final compensation amount Ux(t) obtained, and obtains the position Xz of the bearing; The position Xz of the bearing is obtained by the following formula: ; Where, Xz(t) represents the position of the bearing at time t, and Xz(t-1) represents the position of the bearing at time t-1; The speed and acceleration adjustment unit adjusts the bearing speed Vx and the bearing acceleration ax in real time according to the corrected bearing position Xz; The bearing speed Vx is obtained by the following formula: ; Where Vx(t) represents the bearing speed at time t; The bearing acceleration ax is obtained by the following formula: ; Where ax(t) represents the bearing acceleration at time t; According to the real-time feedback of the bearing speed Vx and the bearing acceleration ax, the compensation strategy is dynamically adjusted to regulate the changes of the bearing speed Vx and the bearing acceleration ax to maintain the normal state of the bearing within a fixed period.

[0046] The feedback and status update module includes a device status collection and analysis unit and a compensation strategy adjustment and update unit; The equipment status collection and analysis unit collects the feedback data of the bearing in real time through sensors, including the new motion deviation nPx and the new bearing acceleration nax, processes and evaluates the collected new motion deviation nPx and the new bearing acceleration nax, analyzes the deviation between the motion accuracy and acceleration of the bearing and the target position, obtains the state error index ESt, and compares it with the preset error threshold Tes to determine the compensation state of the bearing; The state error index ESt is obtained by the following formula: ; The compensation status of the bearing is obtained by matching: When the state error index ESt ≤ error threshold Tes, it means that the bearing is in normal condition and no compensation is required; When the state error index ESt>error threshold Tes, it means that the bearing state is abnormal and compensation is required.

[0047] In this embodiment, the motion trajectory of the bearing is adjusted in real time according to the compensation amount Ux(t) by the motion trajectory correction unit. This trajectory correction based on the real-time compensation amount ensures that the equipment can always move accurately along the predetermined path during operation, avoiding trajectory deviations caused by changes in the external environment or fluctuations in the equipment state. Compared with the traditional control system that relies on fixed trajectory planning, this adaptive correction method can better cope with dynamic changes in the equipment and improve the accuracy and flexibility of the system. The speed and acceleration adjustment unit dynamically adjusts the speed and acceleration of the bearing according to the corrected bearing position Xz. This enables the system to optimize the operating state of the bearing based on real-time feedback, avoiding the loss of accuracy caused by unstable motion or uneven speed in traditional control systems. Through continuous speed and acceleration adjustment, the system can maintain the normal state of the bearing within a fixed period, ensuring efficient operation and precision control of the equipment.

[0048] The dynamic compensation mechanism in this embodiment combines the real-time feedback of the bearing speed Vx and the bearing acceleration ax to continuously optimize the compensation strategy during the operation of the equipment. By continuously adjusting the changes in speed and acceleration, the system can compensate according to the actual motion state of the equipment to maintain the equipment in the optimal operating state at all times. This flexible feedback mechanism enables the equipment to respond to environmental changes and unstable factors in operation in real time, avoiding the decline in system performance due to equipment aging or external changes. The equipment status collection and analysis unit evaluates the motion accuracy of the equipment by collecting the motion deviation and acceleration data of the bearing in real time and calculating the state error index ESt. When the state error index ESt exceeds the preset error threshold, the system can automatically identify equipment abnormalities and make necessary compensation. This precise state evaluation and judgment mechanism ensures that the equipment can be adjusted in time when the state deviation is large, reduces unnecessary compensation or ignores potential control problems, and improves the response speed and stability of the system.

[0049] By comparing the state error index ESt with the error threshold Tes, the system can respond promptly when the bearing state is abnormal, thereby avoiding further accumulation of system errors or equipment damage. This fault warning and recovery capability can reduce downtime and production losses caused by equipment deviations, and improve equipment reliability and production efficiency. The automated compensation mechanism enables the equipment to self-adjust when deviations occur, ensuring continuous high-precision operation.

[0050] Example 6 This embodiment is explained in Example 5. Please refer to Figure 1 ,Specifically: the compensation strategy adjustment and updating unit readjusts the compensation strategy according to the ,acquired state error index ESt; When the state error index ESt> the error threshold Tes, based on the state error index ESt of the bearing state evaluation result, the final compensation amount Ux(t) is re-evaluated and adjusted accordingly to obtain a new compensation amount nUx; The new compensation value nUx is obtained by the following formula: ; Where Kn represents the adjustment factor of the compensation amount.

[0051] The performance evaluation and optimization module evaluates the overall performance of the system based on the error value Ex, the new compensation value nUx and the error change trend Etr, obtains the system performance score PF, and compares it with the preset performance score threshold Tpf to determine the effectiveness of the current control strategy; The system performance score PF is obtained by the following formula: ; Where Tp represents the evaluation period, represent the preset weight values ​​of the error value Ex, the new compensation amount nUx and the error change trend Etr respectively, and ; The effectiveness of the control strategy is obtained by matching: When the system performance score PF ≥ the performance score threshold Tpf, it means that the control strategy has met the requirements and does not need to be adjusted; When the system performance score PF is less than the performance score threshold Tpf, it means that the control strategy does not meet the requirements and needs to be adjusted to adjust the new compensation amount nUx and obtain the adjusted compensation amount TnUx; The adjusted compensation amount TnUx is obtained by the following formula: ; Where C represents the compensation factor.

[0052] In this embodiment, the compensation strategy is dynamically adjusted through the state error index ESt. When the state error index ESt exceeds the preset threshold Tes, the system will re-evaluate and adjust the final compensation amount Ux(t based on the real-time status of the device. This mechanism enables the system to adjust the compensation amount in time according to the current operating status of the device, so as to respond quickly when the device is abnormal, thereby improving the system's adaptability and accuracy.

[0053] The introduction of the system performance score PF makes the optimization of the compensation strategy more intelligent. By comprehensively evaluating the error value Ex, the new compensation amount nUx and the error change trend Etr, the system can quantitatively judge the effectiveness of the current control strategy. If the current performance score is lower than the preset threshold, the system will automatically optimize the control strategy and adjust the compensation amount nUx to improve the overall performance of the system. This adaptive adjustment process avoids the problems of inaccurate control or inefficiency that may be caused by static adjustments in traditional systems. The performance evaluation and optimization module evaluates the effectiveness of the control strategy based on real-time data and makes optimization adjustments as needed. This real-time feedback and adjustment mechanism ensures that the system can maintain the best state at any time. Regardless of how the device status changes, the system can adjust the compensation strategy according to the performance score to ensure that the device always operates efficiently and accurately in complex environments.

[0054] This embodiment sets the threshold for control strategy adjustment and the performance score threshold Tpf to judge the effectiveness of the control strategy, thereby avoiding overcompensation or overly drastic control adjustments. The system dynamically adjusts the compensation strategy according to changes in the error score to ensure that no unnecessary overreaction occurs during the control process, thereby reducing the occurrence of instability. This not only improves the stability of the system, but also improves the accuracy of control. By optimizing the control strategy and dynamically adjusting the compensation amount, the system can maintain high efficiency and reliability under different operating conditions. For example, when a deviation occurs in the equipment, the compensation strategy can be corrected in time, reducing the risk of error accumulation and avoiding the occurrence of equipment failure. Continuous optimization and adjustment of the compensation strategy improves the overall operating efficiency of the equipment and ensures stability in long-term operation.

[0055] Example 7 A multi-axis motion control method for automation equipment, please refer to Figure 2 , specifically: including the following steps: Step 1: The data acquisition and processing module collects data in the multi-axis control system through sensors, fits it into an original data group AW, and performs preprocessing to obtain a multi-axis data group DW; Step 2: The error detection and analysis module performs real-time error detection based on the acquired multi-axis data set DW to obtain the error value Ex and the error change trend Etr; Step 3: The adaptive controller design module designs an adaptive controller to generate a compensation strategy based on the obtained error value Ex and error change trend Etr, obtains the response compensation amount Udy, and calculates the final compensation amount Ux(t); Step 4: The compensation adjustment and motion control module adjusts the motion trajectory, bearing speed Vx and bearing acceleration ax of each bearing according to the final compensation amount Ux(t) obtained, performs real-time compensation, and feeds back to the compensation strategy; Step 5: After the real-time compensation is completed, the feedback and status update module collects the device feedback data, readjusts the compensation strategy, and obtains the new compensation amount nUx; Step 6: The performance evaluation and optimization module evaluates the overall performance of the system based on the error value Ex, the new compensation amount nUx and the error change trend Etr, obtains the system performance score PF, and adjusts the control strategy to obtain the adjusted compensation amount TnUx.

[0056] In this embodiment, the data acquisition and processing module uses sensors to collect various types of data in the multi-axis control system in real time, and converts them into multi-axis data groups DW through preprocessing and standardization, ensuring that the data used by the system has high quality, accuracy and timeliness. By removing noise, outliers and standardizing, the system can reduce data interference and improve the reliability of subsequent analysis and control, thereby ensuring the accuracy and effectiveness of the compensation strategy.

[0057] The error detection and analysis module can analyze the error value Ex and error change trend Etr in the motion system based on real-time data, and perform dynamic detection. This method can accurately evaluate the real-time operating status of the equipment, promptly detect error accumulation or deviation, and ensure that the system can make timely corrections when errors occur. This precise error analysis greatly improves the stability and control accuracy of the equipment's motion. The compensation adjustment and motion control module adjusts the motion trajectory, speed and acceleration of each bearing based on the final compensation amount, so that the system can respond to changes in the motion state of the equipment in real time. This adjustment not only reduces the error caused by changes in the equipment state, but also enables the equipment to maintain the optimal operating trajectory, reduces instability and irregularity during the motion process, and thus improves the stability and accuracy of the system.

[0058] The performance evaluation and optimization module regularly evaluates the overall system performance based on the error value, new compensation amount and error change trend, and calculates the system's performance score PF. If the system performance score is lower than the preset threshold, the module will automatically adjust the compensation strategy. This performance evaluation and optimization capability based on real-time feedback enables the system to continuously improve performance and reduce system errors throughout the entire operation process, ensuring that the equipment can operate efficiently and stably under any operating conditions.

[0059] 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 multi-axis motion control system for automation equipment, characterized in that: It includes data acquisition and processing module, error detection and analysis module, adaptive controller design module, compensation adjustment and motion control module, feedback and state update module and performance evaluation and optimization module; The data acquisition and processing module collects data from the multi-axis control system through sensors, fits it into an original data group AW, and performs preprocessing to obtain a multi-axis data group DW; The error detection and analysis module performs real-time error detection based on the acquired multi-axis data set DW, and obtains the error value Ex and the error change trend Etr; The adaptive controller design module designs an adaptive controller to generate a compensation strategy based on the obtained error value Ex and error change trend Etr, obtains the response compensation amount Udy, and calculates the final compensation amount Ux(t); The compensation adjustment and motion control module adjusts the motion trajectory, bearing speed Vx and bearing acceleration ax of each bearing according to the final compensation amount Ux(t) obtained, performs real-time compensation, and feeds back to the compensation strategy; After the real-time compensation is completed, the feedback and status update module collects the device feedback data, readjusts the compensation strategy, and obtains the new compensation amount nUx; The performance evaluation and optimization module evaluates the overall performance of the system based on the error value Ex, the new compensation amount nUx and the error change trend Etr, obtains the system performance score PF, and adjusts the control strategy to obtain the adjusted compensation amount TnUx.

2. A multi-axis motion control system for automation equipment according to claim 1, characterized in that: The data acquisition and processing module includes a data acquisition unit and a data preprocessing unit; The data acquisition unit collects the bearing data through sensors, including bearing temperature Ta, bearing acceleration ax, bearing load La and motion deviation Px, and fits them into the original data group AW; Among them, the bearing temperature Ta is acquired through the temperature sensor, which can detect the temperature changes caused by friction and load factors during the operation of the equipment; The bearing acceleration ax is acquired through the acceleration sensor; The bearing load La is acquired through the load sensor, and the bearing load La reflects the working status of each axis; The motion deviation Px is acquired through the position sensor, reflecting the difference between the actual position Xact of the bearing and the target position Xtar; The motion deviation Px is obtained by the following formula: ； The data preprocessing unit cleans and standardizes the acquired raw data set AW to obtain a multi-axis data set DW; Cleaning includes filtering and outlier processing. The filtering process removes noise and interference in the original data set AW by using a filter; the outlier processing removes outliers in the original data set AW by using an outlier detection algorithm. Standardization processing uses standardization methods to convert data into a uniform scale to obtain a multi-axis data set DW; The multi-axis data set DW is obtained by the following formula: ； Wherein, DWb represents the b-th data item in the multi-axis data group DW, AWb represents the b-th data item in the original data group AW, μAWb represents the mean of the b-th data item in the original data group AW, and σAWb represents the standard deviation of the b-th data item in the original data group AW.

3. A multi-axis motion control system for automation equipment according to claim 2, characterized in that: The error detection and analysis module includes a data feature extraction unit and an error acquisition unit: The data feature extraction unit extracts features from the multi-axis data set DW, extracts features that affect motion accuracy and control effect, including temperature change rate ΔTa, load change rate ΔLa and motion deviation change rate ΔPx, and fits them into a change feature set LP; The temperature change rate ΔTa is obtained by the following formula: ； Where, Ta(t) represents the bearing temperature at time t, Ta(t-1) represents the bearing temperature at time t-1, and Δt represents the time interval; The load change rate ΔLa is obtained by the following formula: ； Where, La(t) represents the bearing load at time t, and La(t-1) represents the bearing load at time t-1; The motion deviation change rate ΔPx is obtained by the following formula: ； Where, Px(t) represents the motion deviation at time t, and Px(t-1) represents the motion deviation at time t-1; The error acquisition unit calculates and acquires the error value Ex according to the acquired temperature change rate ΔTa, load change rate ΔLa and motion deviation change rate ΔPx, and dynamically analyzes the error value Ex, smoothes the error curve through time series analysis, and identifies the error change trend Etr; The error value Ex is obtained by the following formula: ； ； In the formula, represent the preset weight values ​​of the temperature change rate ΔTa, the load change rate ΔLa and the motion deviation change rate ΔPx, respectively, and , fin represents the interaction function between features, Represents the interaction coefficient of the temperature change rate ΔTa and the load change rate ΔLa, Represents the interaction coefficient of the load change rate ΔLa and the motion deviation change rate ΔPx, Represents the interaction coefficient between the temperature change rate ΔTa and the motion deviation change rate ΔPx; The error change trend Etr is obtained by the following formula: ； Where Ex(ti) represents the error value at time ti, n represents the time window size for calculating the error trend, and i represents the index variable used to traverse the past n time points.

4. The multi-axis motion control system for automation equipment according to claim 1, characterized in that: The adaptive controller design module includes an error response design unit and a dynamic compensation adjustment unit; The error response design unit designs the error response function based on the obtained error value Ex and error change trend Etr, combined with PID control, to obtain the error compensation amount Uex(t); The error compensation amount Uex (t) is obtained by the following formula: ； In the formula, Ex represents the error value at time t, Kp represents the proportional gain, Ki represents the integral gain, Kd represents the differential gain, dt represents the integral, represents the rate of change of error at time t; The error compensation amount Uex(t) obtained is combined with the error change trend Etr, and the error change trend Etr is used as a dynamic weight adjustment compensation strategy to obtain the response compensation amount Udy; Among them, the error change trend Etr can affect the amplitude of the compensation response; When the error value Ex continues to increase within a fixed period, the controller needs to increase its response; When the error value Ex remains stable within a fixed period, the controller reduces the response; The response compensation amount Udy is obtained by the following formula: ； Where fq represents the trend change function.

5. A multi-axis motion control system for automation equipment according to claim 4, characterized in that: The dynamic compensation adjustment unit obtains the final compensation amount Ux(t) based on the obtained response compensation amount Udy, combined with the temperature change rate ΔTa and the load change rate ΔLa; The temperature compensation value Uta is obtained by the influence of the temperature change rate ΔTa on the bearing motion performance; The temperature compensation value Uta is obtained by the following formula: ； In the formula, Indicates the sensitivity coefficient of temperature change to the compensation amount; Obtain the load compensation amount Ula through the influence of the load change rate ΔLa on the bearing stability and motion accuracy; The load compensation amount Ula is obtained by the following formula: ； In the formula, Indicates the influence coefficient of load change on compensation amount; Combine the temperature compensation Uta and the load compensation Ula to obtain the final compensation Ux (t); The final compensation amount Ux(t) is obtained by the following formula: ； Where k1 and k2 represent adjustment coefficients.

6. A multi-axis motion control system for automation equipment according to claim 5, characterized in that: The compensation adjustment and motion control module includes a motion trajectory correction unit and a speed and acceleration adjustment unit; The motion trajectory correction unit adjusts and corrects the motion trajectory of the bearing in real time according to the final compensation amount Ux(t) obtained, and obtains the position Xz of the bearing; The position Xz of the bearing is obtained by the following formula: ； Where, Xz(t) represents the position of the bearing at time t, and Xz(t-1) represents the position of the bearing at time t-1; The speed and acceleration adjustment unit adjusts the bearing speed Vx and the bearing acceleration ax in real time according to the corrected bearing position Xz; The bearing speed Vx is obtained by the following formula: ； Where Vx(t) represents the bearing speed at time t; The bearing acceleration ax is obtained by the following formula: ； Where ax(t) represents the bearing acceleration at time t; According to the real-time feedback of the bearing speed Vx and the bearing acceleration ax, the compensation strategy is dynamically adjusted to regulate the changes of the bearing speed Vx and the bearing acceleration ax to maintain the normal state of the bearing within a fixed period.

7. The multi-axis motion control system for automation equipment according to claim 1, characterized in that: The feedback and status update module includes a device status collection and analysis unit and a compensation strategy adjustment and update unit; The equipment status collection and analysis unit collects the feedback data of the bearing in real time through sensors, including the new motion deviation nPx and the new bearing acceleration nax, processes and evaluates the collected new motion deviation nPx and the new bearing acceleration nax, analyzes the deviation between the motion accuracy and acceleration of the bearing and the target position, obtains the state error index ESt, and compares it with the preset error threshold Tes to determine the compensation state of the bearing; The state error index ESt is obtained by the following formula: ； The compensation status of the bearing is obtained by matching: When the state error index ESt ≤ the error threshold Tes, it means that the bearing is in normal condition and no compensation is required; When the state error index ESt>error threshold Tes, it means that the bearing state is abnormal and compensation is required.

8. A multi-axis motion control system for automation equipment according to claim 7, characterized in that: The compensation strategy adjustment and update unit readjusts the compensation strategy according to the acquired state error index ESt; When the state error index ESt>error threshold Tes, based on the state error index ESt of the bearing state evaluation result, the final compensation amount Ux(t) is re-evaluated and adjusted accordingly to obtain a new compensation amount nUx; The new compensation value nUx is obtained by the following formula: ； Where Kn represents the adjustment factor of the compensation amount.

9. A multi-axis motion control system for automation equipment according to claim 8, characterized in that: The performance evaluation and optimization module evaluates the overall performance of the system based on the error value Ex, the new compensation value nUx and the error change trend Etr, obtains the system performance score PF, and compares it with the preset performance score threshold Tpf to determine the effectiveness of the current control strategy; The system performance score PF is obtained by the following formula: ； Where Tp represents the evaluation period, represent the preset weight values ​​of the error value Ex, the new compensation amount nUx and the error change trend Etr respectively, and ; The effectiveness of the control strategy is obtained by matching: When the system performance score PF ≥ the performance score threshold Tpf, it means that the control strategy has met the requirements and does not need to be adjusted; When the system performance score PF is less than the performance score threshold Tpf, it means that the control strategy does not meet the requirements and needs to be adjusted to adjust the new compensation amount nUx and obtain the adjusted compensation amount TnUx; The adjusted compensation amount TnUx is obtained by the following formula: ； Where C represents the compensation factor.

10. A multi-axis motion control method for automation equipment, applied to a multi-axis motion control system for automation equipment according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: The data acquisition and processing module collects data in the multi-axis control system through sensors, fits it into an original data group AW, and performs preprocessing to obtain a multi-axis data group DW; Step 2: The error detection and analysis module performs real-time error detection based on the acquired multi-axis data set DW to obtain the error value Ex and the error change trend Etr; Step 3: The adaptive controller design module designs an adaptive controller to generate a compensation strategy based on the obtained error value Ex and error change trend Etr, obtains the response compensation amount Udy, and calculates the final compensation amount Ux(t); Step 4: The compensation adjustment and motion control module adjusts the motion trajectory, bearing speed Vx and bearing acceleration ax of each bearing according to the final compensation amount Ux(t) obtained, performs real-time compensation, and feeds back to the compensation strategy; Step 5: After the real-time compensation is completed, the feedback and status update module collects the device feedback data, readjusts the compensation strategy, and obtains the new compensation amount nUx; Step 6: The performance evaluation and optimization module evaluates the overall performance of the system based on the error value Ex, the new compensation amount nUx and the error change trend Etr, obtains the system performance score PF, and adjusts the control strategy to obtain the adjusted compensation amount TnUx.

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