A method and system for nonlinear electromechanical servo control based on orthogonal characteristics

Abstract

The invention discloses an electromechanical servo nonlinear control method and system based on orthogonal characteristics, and relates to the technical field of electromechanical servo control, including: three-dimensional modeling of an electromechanical servo system to obtain its nonlinear characteristics and key parameters; establishing a nonlinear characteristic set, extracting characteristic data from historical data and determining its standard range; dividing each characteristic data into different levels, using the orthogonal analysis method to perform multiple experimental simulations, calculating the range to identify key characteristic data and key levels, and screening out experimental data with a movement deviation less than a threshold; integrating all the key data of nonlinear characteristics, performing experimental simulations again using the orthogonal analysis method, selecting the optimal characteristic data group, and adjusting the electromechanical servo system accordingly to achieve effective control of the nonlinear characteristics and improve system performance and stability; and providing an effective solution for the nonlinear control of the electromechanical servo system through fine characteristic data analysis and optimized simulation.

Description

Technical Field

[0001] The invention relates to the technical field of electromechanical servo control, in particular to an electromechanical servo nonlinear control method and system based on orthogonal characteristics. Background Art

[0002] In the control field of electromechanical servo systems, with the continuous development of science and technology, the requirements for system performance and stability are increasing day by day; electromechanical servo systems, as core components of industrial automation, aerospace, robotics and other fields, their performance directly affects the operating efficiency and reliability of the entire system; however, electromechanical servo systems often face complex nonlinear characteristics in practical applications, such as clearance, friction, elastic deformation, etc. These characteristics have a significant impact on the static and dynamic performance of the system, and are likely to lead to increased tracking errors, drive delays, low-speed "creeping" or limit cycle oscillations, thereby limiting the improvement of system performance;

[0003] Traditional control methods, such as PID control, have been successful in many industrial applications, but they are incapable of dealing with the nonlinear characteristics of electromechanical servo systems. PID control relies on the linear model of the system, and its parameters are difficult to determine for nonlinear systems, and it cannot adapt to complex high-precision control situations.

[0004] Traditional electromechanical servo nonlinear control methods often control a single nonlinear characteristic in the electromechanical servo system, while ignoring the interaction and influence between multiple nonlinear characteristics in the system. This local optimization method is difficult to achieve the global optimal control effect; in addition, the adjustment of parameters usually relies on experience or trial and error, which is not only time-consuming and labor-intensive, but also difficult to ensure that the adjusted parameters can reach the optimal state. Similarly, for multiple parameters in the system, traditional methods are often difficult to optimize simultaneously. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In response to the technical problems in the background technology, the present invention proposes an electromechanical servo nonlinear control method and system based on orthogonal characteristics, which comprehensively obtain the nonlinear characteristics and key parameters of the electromechanical servo system; use the orthogonal analysis method to systematically analyze and optimize the key parameters under various nonlinear characteristics, and identify the key characteristic data and key levels that affect the operating accuracy of the servo motor; through experimental verification and parameter adjustment, precise control of the electromechanical servo system is achieved; thereby solving the technical problems recorded in the background technology.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] A method for controlling an electromechanical servo nonlinear system based on orthogonal characteristics, comprising:

[0010] Conduct three-dimensional modeling of the electromechanical servo system; obtain the nonlinear characteristics of the electromechanical servo system and obtain the key parameters under each nonlinear characteristic;

[0011] Establish a nonlinear characteristic set, each of which contains a corresponding characteristic data set; obtain multiple sets of characteristic data during normal operation and abnormal operation from historical operation data, and obtain a standard value range for each characteristic data; select characteristic values ​​for each characteristic data and form a corresponding characteristic data set;

[0012] Assign different levels to the data in each feature data set; perform multiple experimental simulations of feature data at different levels based on the orthogonal analysis method, calculate the range of each feature data based on the obtained moving deviation value, and identify the key levels under the key feature data; filter out the experimental data at these key levels, and filter out all experimental data with moving deviation values ​​less than the moving deviation threshold;

[0013] All experimental data screened out by nonlinear characteristics are combined, and experimental simulation is performed again based on the orthogonal analysis method to screen out the final characteristic data group, and corresponding adjustments are made in the electromechanical servo system.

[0014] Specifically, the nonlinear characteristics obtained include gap nonlinear characteristics, friction nonlinear characteristics, elastic deformation nonlinear characteristics, dead zone nonlinear characteristics and saturation nonlinear characteristics;

[0015] The key parameters of the gap nonlinear characteristics are transmission clearance and preload; the key parameters of the friction nonlinear characteristics are friction coefficient and lubrication index; the key parameters of the elastic deformation nonlinear characteristics are elastic modulus and coupling stiffness; the key parameters of the dead zone nonlinear characteristics are sensor sensitivity and actuator resolution; the key parameters of the saturation nonlinear characteristics are power amplifier gain and control algorithm parameters.

[0016] Furthermore, the lubrication index Based on the amount of lubricant used on the sliding surfaces in the transmission mechanism, rolling bearings, and the rotor and stator surfaces in the servo motor , Coverage area ratio on friction surface And replacement cycle To determine, the expression is: ,in, , , Respectively indicate the amount of lubricant , Coverage area ratio on friction surface And replacement cycle The preset scaling factor.

[0017] Furthermore, the gap nonlinear characteristic set is , Indicates Transmission clearance datasets between gears or bearings, Indicates A gear or bearing preload data set, Indicates the number of adjacent gears or adjacent bearings, or the total number of adjacent gears and bearings. Represents the total number of gears and bearings; the transmission clearance data set and preload data set are the characteristic data sets of the clearance nonlinear characteristics;

[0018] The friction nonlinear characteristic set is , Indicates The friction coefficient dataset at the friction surface is Indicates Lubrication index dataset at friction surfaces, It represents the total number of sliding surfaces, rolling bearing surfaces in the transmission mechanism, and the friction surfaces between the rotor and the stator in the servo motor; the friction coefficient data set and the lubrication index data set are the characteristic data sets of the friction nonlinear characteristics;

[0019] The nonlinear characteristic set of elastic deformation is ,in, Indicates The elastic modulus data set of the coupling, Indicates Coupling stiffness dataset for a coupling, Represents the total number of couplings; the elastic modulus data set and the coupling stiffness data set are the characteristic data sets of the nonlinear characteristics of elastic deformation;

[0020] The dead zone nonlinear characteristic set is ,in, Indicates The sensitivity dataset of sensors, Indicates The resolution dataset of the actuators is Indicates the total number of sensors, represents the total number of actuators; the sensitivity data set and the resolution data set are the characteristic data sets of the dead zone nonlinear characteristics;

[0021] The saturated nonlinear characteristic set is ,in, represents the output voltage gain data set of the power amplifier, represents the output current gain data set of the power amplifier, represents the proportional gain data set, represents the integration time constant data set, represents a differential time constant data set; wherein the output voltage gain data set, the output current gain data set, the proportional gain data set, the integral time constant data set and the differential time constant data set are characteristic data sets of saturated nonlinear characteristics.

[0022] Furthermore, multiple sets of characteristic data of normal operation are obtained from the historical operation data of the electromechanical servo system. Normal operation refers to the operation process when the movement deviation of the servo motor after executing the instruction is less than a preset movement deviation threshold. The movement deviation is obtained based on the Euclidean distance between the actual position of the servo motor after the movement is completed in the global coordinate system and the target position that should have been reached.

[0023] Acquire multiple sets of the above characteristic data during abnormal operation from the historical operation data of the electromechanical servo system, wherein the abnormal operation refers to the operation process when the movement deviation of the servo motor after executing the instruction is not less than a preset movement deviation threshold;

[0024] Obtain the value range of each characteristic data when the servo motor operates normally; obtain the value range of each characteristic data when the servo motor operates abnormally and determine that the cause of the abnormal operation is the abnormality of the corresponding characteristic data; combine the value range of each characteristic data when the servo motor operates normally with the value range when the servo motor operates abnormally to obtain the standard value range of each characteristic data.

[0025] Furthermore, the method for determining the standard numerical range is specifically as follows: remove the numerical range corresponding to the intersection of the numerical range during normal operation and the numerical range during abnormal operation from the numerical range during normal operation of the servo motor, and obtain the standard numerical range of each characteristic data; if the numerical range of the characteristic data during abnormal operation of the servo motor includes the numerical range during normal operation, it is necessary to divide the numerical range during abnormal operation into blocks, and if the difference between two adjacent numerical values ​​exceeds a preset difference threshold, the numerical range during abnormal operation is divided into two blocks, the maximum value of the numerical range of the first part is the smaller of the two numerical values, and the minimum value of the numerical range of the second part is the larger of the two numerical values.

[0026] Further, each characteristic data is taken out in turn, and other characteristic data are set according to standard values, and simulation is performed in a three-dimensional model of the electromechanical servo system, wherein the standard value is the median value of the standard value range of each characteristic data;

[0027] Starting from the minimum value in the standard numerical range of the selected characteristic data, the operation simulation of the servo motor is performed in sequence, and the movement deviation after simulation is obtained; based on the relationship between the movement deviation after simulation and the movement deviation threshold, the standard numerical range is divided into two or three parts; the numerical range in which the movement deviation after simulation does not exceed the movement deviation threshold is recorded as the first numerical range, and the numerical range in which the movement deviation after simulation exceeds the movement deviation threshold is recorded as the second numerical range;

[0028] The median values ​​of each feature data within the first numerical range and the second numerical range are combined into data sets corresponding to the feature data according to the size of the data, that is, each feature data set in the nonlinear characteristic set.

[0029] Further, each feature data set in each type of nonlinear characteristic set is obtained in turn, and a corresponding level is assigned to each data, specifically recording these data as small or low feature data, medium feature data, and large or high feature data according to their size;

[0030] Experimental simulation is performed using the combination method of all characteristic data in nonlinear characteristics at different levels; for the gap nonlinear characteristic set, if there is A feature data set contains 2 data, then a total of The experimental simulation is performed, and the calculation method of the experimental times of the remaining nonlinear characteristic sets is the same; after each experimental simulation, the moving deviation value obtained by analysis is recorded;

[0031] For each feature data set in the nonlinear characteristics, the moving deviation mean value at each level is calculated; the range of the moving deviation mean values ​​at all levels in each feature data set is calculated, that is, the difference between the maximum moving deviation mean value and the minimum moving deviation mean value under the feature data;

[0032] The characteristic data with a range greater than a preset range threshold is regarded as the key characteristic data affecting the running accuracy of the servo motor; for each key characteristic data, the level with the smallest moving deviation average is recorded as the key level.

[0033] Specifically, the key levels of all key characteristic data of each nonlinear characteristic are obtained, the experimental data under these key levels are selected from all experimental simulations, and the characteristic data under all experimental data whose moving deviation values ​​are less than the moving deviation threshold are screened out;

[0034] Combine all the characteristic data under the experimental data selected from all nonlinear characteristics, and perform experimental simulation based on the selected characteristic data. If the gap nonlinear characteristics, friction nonlinear characteristics, elastic deformation nonlinear characteristics, dead zone nonlinear characteristics and saturation nonlinear characteristics are selected respectively , , , , group data, then a total of Experimental simulations are performed; the experimental data with the smallest movement deviation value is selected from the results of these experimental simulations, and the various components and parameters in the electromechanical servo system are adjusted according to the characteristic data in this set of experimental data.

[0035] An electromechanical servo nonlinear control system based on orthogonal characteristics, comprising:

[0036] The data acquisition module performs three-dimensional modeling on the electromechanical servo system; obtains the nonlinear characteristics of the electromechanical servo system and obtains the key parameters under each nonlinear characteristic;

[0037] The characteristic data determination module establishes a nonlinear characteristic set, each of which contains a corresponding characteristic data set; obtains multiple sets of characteristic data during normal operation and abnormal operation from historical operation data, and obtains a standard value range for each characteristic data; selects characteristic values ​​for each characteristic data, and forms a corresponding characteristic data set;

[0038] The key feature identification module assigns different levels to the data in each feature data set; performs multiple experimental simulations of multiple sets of feature data at different levels based on the orthogonal analysis method, calculates the range of each feature data based on the obtained moving deviation value, and identifies the key levels under the key feature data; screens out the experimental data under these key levels, and screens out all experimental data with moving deviation values ​​less than the moving deviation threshold;

[0039] The comprehensive simulation control module combines all the experimental data screened out by nonlinear characteristics, performs experimental simulation again based on orthogonal analysis, screens out the final characteristic data set, and makes corresponding adjustments in the electromechanical servo system.

[0040] (III) Beneficial effects

[0041] The present invention provides an electromechanical servo nonlinear control method and system based on orthogonal characteristics, which has the following beneficial effects:

[0042] 1. Through sophisticated 3D modeling and comprehensive nonlinear characteristic analysis, multiple orthogonal nonlinear characteristics and their key parameters are innovatively identified and optimized, which not only ensures the accurate simulation of each component and connection relationship of the electromechanical servo system, but also deeply analyzes the nonlinear characteristics such as clearance, friction, elastic deformation, dead zone and saturation, and specifically adjusts key parameters such as transmission clearance, friction coefficient, elastic modulus, etc., to achieve independent control and optimization of each nonlinear characteristic. This orthogonal characteristic control method greatly improves the control accuracy, response speed and stability of the electromechanical servo system;

[0043] 2. By constructing a comprehensive set of nonlinear characteristics and finely dividing the feature data set, the standard value range of each feature is accurately defined in combination with historical operation data, which enables in-depth analysis and precise control of the nonlinear characteristics of the electromechanical servo system. It not only effectively identifies the difference in feature data between normal operation and abnormal operation, but also optimizes the selection of feature values ​​through simulation, ensuring the pertinence and effectiveness of the control strategy, significantly improving the fault diagnosis capability and operation stability of the electromechanical servo system, and providing strong technical support for the control of complex nonlinear systems.

[0044] 3. By finely dividing the characteristic data levels and using the orthogonal analysis method for multiple rounds of experimental simulations, the key characteristic data and their optimal levels were effectively identified; not only the operating accuracy of the servo motor was significantly improved, but also the superiority of the final characteristic data group was ensured through layer-by-layer screening and optimization, providing a scientific basis for the precise adjustment of the electromechanical servo system; the control strategy based on orthogonal characteristics greatly enhanced the system's control ability over nonlinear characteristics and achieved performance optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic diagram of the steps of an electromechanical servo nonlinear control method based on orthogonal characteristics provided by the present invention;

[0046] Figure 2 A flowchart of an electromechanical servo nonlinear control method based on orthogonal characteristics provided by the present invention;

[0047] Figure 3 A schematic structural diagram of an electromechanical servo nonlinear control system based on orthogonal characteristics provided by the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments 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.

[0049] refer to Figure 1 and Figure 2 The present invention provides an electromechanical servo nonlinear control method based on orthogonal characteristics, comprising:

[0050] Step 1: Perform three-dimensional modeling on the electromechanical servo system; obtain the nonlinear characteristics of the electromechanical servo system, and obtain key parameters under each nonlinear characteristic;

[0051] The step one includes the following steps:

[0052] Step 101, obtaining the structural design drawings of each component in the electromechanical servo system and the connection design drawings between each component. The components in the electromechanical servo system include mechanical parts including controllers, drivers, servo motors, transmission mechanisms, sensors, power supplies and other components, wherein the controller is responsible for receiving signals or instructions from the outside, and sending control signals to the driver after internal processing; the driver is responsible for converting the weak current control signal from the controller into the strong current drive signal required by the servo motor; the servo motor is responsible for precise rotation or linear motion according to the drive signal from the driver; the transmission mechanism converts the rotation or linear motion of the servo motor into the motion form required by the load; the sensor is responsible for real-time monitoring of the load's position, speed and other status information, and feeding this information back to the controller; the power supply is responsible for providing power to the entire electromechanical servo system;

[0053] Based on the structural design drawings of the above-mentioned components, three-dimensional modeling is performed on each component, and based on the connection design drawings between the components, the three-dimensional models of each component are spliced ​​to obtain a three-dimensional model of the electromechanical servo system; based on the control strategy of the electromechanical servo system, motion simulation, control algorithm visualization, virtual debugging and testing functions of the three-dimensional model of the electromechanical servo system are realized, and the nonlinear characteristics of the electromechanical servo system are controlled;

[0054] Step 102, obtaining multiple nonlinear characteristics of the electromechanical servo system, including gap nonlinear characteristics, friction nonlinear characteristics, elastic deformation nonlinear characteristics, dead zone nonlinear characteristics, and saturation nonlinear characteristics;

[0055] Among them, the gap nonlinear characteristic refers to the discontinuous or sudden change in motion transmission caused by the gap between components in the mechanical system; it is related to the gears and bearings in the transmission mechanism;

[0056] Friction nonlinearity: describes the complex change of friction between contact surfaces with the relative motion speed, direction or contact pressure; it is related to the sliding surface in the transmission mechanism, rolling bearings, and the friction between the rotor and stator in the servo motor;

[0057] Elastic deformation nonlinear characteristics: when a material is deformed by force, the deformation is not proportional to the stress it is subjected to; it is related to the coupling in the transmission mechanism;

[0058] Dead zone nonlinear characteristics: When the input signal changes within a certain range, the output signal remains unchanged, and the response is generated only when the input exceeds a certain threshold; it is related to the position sensor, force sensor and acceleration sensor in the sensor;

[0059] Saturation nonlinear characteristics: When the input signal increases to a certain extent, the output signal no longer increases with the input, but remains near a constant value; it is related to the power amplifier in the driver and the limit value in the control algorithm in the controller;

[0060] Step 103, obtaining key parameters corresponding to each nonlinear characteristic; wherein the key parameters of the gap nonlinear characteristic are transmission gap and preload, the transmission gap directly affects the positioning accuracy and response speed of the system, and the preload optimizes the system performance by adjusting the gap size, both of which are key to reducing the impact of gap nonlinearity; the transmission gap and preload are the transmission gap between each gear or bearing in the electromechanical servo system and the preload of each gear or bearing; directly measure the gap between the gears, bearings and other components in the transmission mechanism by using a micrometer; gradually increase the preload on each gear and bearing component in the transmission mechanism, observe the change in the system response characteristics, and find a suitable preload value;

[0061] The key parameters of friction nonlinearity are friction coefficient and lubrication index. The friction coefficient directly reflects the degree of friction nonlinearity. The lubrication index reduces friction nonlinearity by reducing the friction coefficient. The two together affect the dynamic characteristics of the system. The friction coefficient is the friction between the sliding surface and rolling bearing in the transmission mechanism, and the friction between the rotor and stator in the servo motor. The friction coefficient between the contact surfaces in the transmission mechanism and between the rotor and stator in the servo motor is measured by a friction coefficient measuring instrument. The lubrication index Based on the amount of lubricant used on the sliding surfaces in the transmission mechanism, rolling bearings, and the rotor and stator surfaces in the servo motor , Coverage area ratio on friction surface And replacement cycle To determine, and all lubricants are the same, the expression is: ,in, , , Respectively indicate the amount of lubricant , Coverage area ratio on friction surface And replacement cycle The preset proportional coefficient, the specific value is set by the electromechanical servo system manager based on the correlation of various data;

[0062] The key parameters of elastic deformation nonlinear characteristics are elastic modulus and coupling stiffness. The elastic modulus determines the material's ability to resist deformation, and optimizing the coupling stiffness is used to reduce elastic deformation nonlinearity. Both are related to the stability and accuracy of the system. Based on applying stress to the coupling, measuring the strain generated, and determining the elastic modulus through the ratio of stress to strain. Based on the finite element method, the three-dimensional model of the coupling is meshed, material properties are assigned, loads and boundary conditions are applied, and static analysis is performed through finite element software to obtain the stiffness data of each coupling.

[0063] The key parameters of the dead zone nonlinear characteristics are sensor sensitivity and actuator resolution. Sensor sensitivity affects the system detection accuracy, and actuator resolution determines the system's minimum action unit. The two together determine the dead zone range, which is crucial to the system's response speed and accuracy. By consulting the technical specifications or manuals of the sensors and actuators, the sensitivity of each sensor and the resolution of each actuator can be obtained.

[0064] The key parameters of the saturation nonlinear characteristics are the power amplifier gain and the control algorithm parameters. The power amplifier gain determines the upper limit of the system output, and the control algorithm parameters such as the limit value are used to prevent output saturation. The two together maintain the stability and safety of the system. Use oscilloscopes, power meters and other equipment to measure the output voltage and output current gain of the power amplifier under different inputs. The control algorithm parameters include the values ​​of proportional gain, integral time constant, and differential time constant. By simulating the operating state of the servo motor under different parameters, the saturation nonlinear characteristics are controlled.

[0065] Through sophisticated 3D modeling and comprehensive nonlinear characteristic analysis, multiple orthogonal nonlinear characteristics and their key parameters are innovatively identified and optimized, which not only ensures the accurate simulation of the components and connection relationships of the electromechanical servo system, but also deeply analyzes the nonlinear characteristics such as clearance, friction, elastic deformation, dead zone and saturation, and specifically adjusts key parameters such as transmission clearance, friction coefficient, elastic modulus, etc., to achieve independent control and optimization of each nonlinear characteristic. This orthogonal characteristic control method greatly improves the control accuracy, response speed and stability of the electromechanical servo system.

[0066] Step 2: Establish a nonlinear characteristic set, each nonlinear characteristic set contains a corresponding feature data set; obtain multiple sets of feature data during normal operation and abnormal operation from historical operation data, and obtain a standard value range for each feature data; select feature values ​​for each feature data and form a corresponding feature data set;

[0067] The step 2 includes the following steps:

[0068] Step 201: Put all the data types obtained in step 1 into the corresponding nonlinear characteristic set and use them as the characteristic data of each nonlinear characteristic to obtain the gap nonlinear characteristic set, friction nonlinear characteristic set, elastic deformation nonlinear characteristic set, dead zone nonlinear characteristic set and saturation nonlinear characteristic set, respectively. , , , , Representation includes characteristic data sets under multiple nonlinear characteristics;

[0069] Among them, the gap nonlinear characteristic set for ,in, Indicates Transmission clearance datasets between gears or bearings, Indicates A gear or bearing preload data set, Indicates the number of adjacent gears or adjacent bearings, or the total number of adjacent gears and bearings. Represents the total number of gears and bearings; the transmission clearance data set and preload data set are the characteristic data sets of the clearance nonlinear characteristics;

[0070] Friction Nonlinearity Property Set for ,in, Indicates The friction coefficient data set at the friction surface includes the sliding surface in the transmission mechanism, the rolling bearing surface, and the friction surface between the rotor and the stator in the servo motor. Indicates Lubrication index dataset at friction surfaces, It represents the total number of sliding surfaces, rolling bearing surfaces in the transmission mechanism, and the friction surfaces between the rotor and the stator in the servo motor; the friction coefficient data set and the lubrication index data set are the characteristic data sets of the friction nonlinear characteristics;

[0071] Elastic deformation nonlinear property set for ,in, Indicates The elastic modulus data set of the coupling, Indicates Coupling stiffness dataset for a coupling, Represents the total number of couplings; the elastic modulus data set and the coupling stiffness data set are the characteristic data sets of the nonlinear characteristics of elastic deformation;

[0072] Dead Zone Nonlinear Characteristics Set for ,in, Indicates The sensitivity dataset of sensors, Indicates The resolution dataset of the actuators is Indicates the total number of sensors, represents the total number of actuators; the sensitivity data set and the resolution data set are the characteristic data sets of the dead zone nonlinear characteristics;

[0073] Saturation nonlinear characteristic set for ,in, represents the output voltage gain data set of the power amplifier, represents the output current gain data set of the power amplifier, represents the proportional gain data set, represents the integration time constant data set, represents a differential time constant data set; wherein the output voltage gain data set, the output current gain data set, the proportional gain data set, the integral time constant data set and the differential time constant data set are characteristic data sets of saturation nonlinear characteristics;

[0074] Step 202, obtaining multiple sets of the above-mentioned characteristic data during normal operation from the historical operation data of the electromechanical servo system, wherein normal operation refers to the operation process when the movement deviation of the servo motor after executing the instruction is less than a preset movement deviation threshold, and the movement deviation refers to the degree of proximity between the expected position and the actual position that the servo motor can reach and maintain, and is obtained based on the Euclidean distance between the actual position of the servo motor after the movement is completed in the global coordinate system and the target position that should have been reached;

[0075] Acquire multiple sets of the above characteristic data during abnormal operation from the historical operation data of the electromechanical servo system, wherein the abnormal operation refers to the operation process when the movement deviation of the servo motor after executing the instruction is not less than a preset movement deviation threshold;

[0076] Based on the multiple sets of characteristic data obtained during normal operation, the numerical range of each characteristic data when the servo motor is operating normally is obtained; based on the multiple sets of characteristic data obtained during abnormal operation, the numerical range of each characteristic data when the servo motor is operating abnormally is obtained, and it is determined that the cause of abnormal operation is the abnormality of the corresponding characteristic data; the numerical range of each characteristic data when the servo motor is operating normally is combined with the numerical range when the servo motor is operating abnormally, and specifically, the numerical range corresponding to the intersection of the numerical range when the servo motor is operating normally and the numerical range when the servo motor is operating abnormally is removed from the numerical range when the servo motor is operating normally, to obtain the standard numerical range of each characteristic data; if the numerical range of the characteristic data when the servo motor is operating abnormally includes the numerical range when the servo motor is operating normally, it is necessary to divide the numerical range when the servo motor is operating abnormally into blocks, and if the difference between two adjacent numerical values ​​F1 and F2 exceeds a preset difference threshold, the numerical range when the abnormal operation is divided into two blocks, the maximum value of the numerical range of the former part is F1, and the minimum value of the numerical range of the latter part is F2;

[0077] Step 203: Since the normal operation of the servo motor in the historical data is determined based on multiple characteristic data, it is necessary to select the characteristic value of each characteristic data, specifically:

[0078] Taking out each characteristic data in turn, setting other characteristic data according to standard values, and performing simulation in a three-dimensional model of the electromechanical servo system, wherein the standard value is the median value of the standard value range of each characteristic data;

[0079] Starting from the minimum value in the standard numerical range of the selected characteristic data, the operation simulation of the servo motor is performed in sequence, and the movement deviation after simulation is obtained; the standard numerical range is divided into two or three parts based on the relationship between the movement deviation after simulation and the movement deviation threshold; when it is detected that the numerical relationship between the movement deviation and the movement deviation threshold after only one simulation changes, the standard numerical range is divided into two parts, and the numerical range in which the movement deviation after simulation does not exceed the movement deviation threshold is recorded as the first numerical range, and the numerical range in which the movement deviation after simulation exceeds the movement deviation threshold is recorded as the second numerical range; when the characteristic data is in the first numerical range, it indicates that the operation effect of the servo motor is good, and when the characteristic data is in the second numerical range, it indicates that the operation effect of the servo motor is general; when it is detected that the numerical relationship between the movement deviation and the movement deviation threshold after two simulations changes, the standard numerical range is divided into three parts, including a first numerical range and two second numerical ranges;

[0080] The first numerical range and the second numerical range of each characteristic data are obtained in turn, and the median of each characteristic data within the first numerical range and the second numerical range constitutes a data set of the corresponding characteristic data according to the size of the data, that is, each characteristic data set in the nonlinear characteristic set in step 201.

[0081] By constructing a comprehensive set of nonlinear characteristics and finely dividing the feature data set, and combining historical operating data to accurately define the standard numerical range of each feature, we have achieved in-depth analysis and precise control of the nonlinear characteristics of the electromechanical servo system. Not only has it effectively identified the difference in feature data under normal operation and abnormal operation, but it has also optimized the selection of feature values ​​through simulation, ensuring the pertinence and effectiveness of the control strategy, significantly improving the fault diagnosis capability and operating stability of the electromechanical servo system, and providing strong technical support for the control of complex nonlinear systems.

[0082] Step 3, assign different levels to the data in each feature data set; perform multiple experimental simulations of feature data at multiple levels based on the orthogonal analysis method, calculate the range of each feature data based on the obtained moving deviation value, and identify the key levels under the key feature data; screen out the experimental data under these key levels, and screen out all experimental data with moving deviation values ​​less than the moving deviation threshold; combine all experimental data screened out by nonlinear characteristics, perform experimental simulation again based on the orthogonal analysis method, screen out the final feature data group, and make corresponding adjustments in the electromechanical servo system;

[0083] The step three includes the following steps:

[0084] Step 301, sequentially obtain each feature data set in each type of nonlinear characteristic set, each feature data set contains 2 or 3 data, assign a corresponding level to each data, and specifically record these data as small or low feature data, medium feature data and large or high feature data according to their size; for example, for the first The transmission clearance data set between the gears or bearings is used to record the three data in the transmission clearance data set as small clearance data, medium clearance data and large clearance data; for the A preload data set of a gear or a bearing, and three data in the preload data set are recorded as low preload data, medium preload data, and high preload data;

[0085] Step 302: Experimentally simulate the characteristic data at different levels in each type of nonlinear characteristics based on the orthogonal analysis method, and use the combination method of all characteristic data in the nonlinear characteristics to simulate the operation of the servo motor; for the gap nonlinear characteristic set, if there is A feature data set contains 2 data, then a total of The experimental simulation is performed, and the calculation method of the experimental times of the remaining nonlinear characteristic sets is the same; after each experimental simulation, the moving deviation value obtained by analysis is recorded;

[0086] For each characteristic data set in the nonlinear characteristics, calculate the average moving deviation at each level; if you want to calculate the average moving deviation at the small gap level, you need to obtain all experimental records of all transmission gaps at the small gap level in the experimental simulation, and perform mean calculation on the moving deviation values ​​obtained after analyzing these experimental records; similarly calculate the average moving deviation at the medium gap level and the large gap level; calculate the range of the moving deviation average at all levels in each characteristic data set, that is, the difference between the maximum moving deviation average and the minimum moving deviation average under the characteristic data;

[0087] Step 303: sort all feature data according to the range of each feature data, and take feature data with a range greater than a preset range threshold as key feature data that affect the running accuracy of the servo motor. The change of these data has a significant impact on the moving deviation. For each key feature data, the level with the smallest moving deviation average value is recorded as the key level. For example, if the first The transmission clearance data set between the gears or bearings is the key feature data, and the moving deviation average value under the small clearance level is the smallest, then the small clearance level in the key feature data is recorded as the key level;

[0088] Step 304: for each nonlinear characteristic, obtain the key levels of all key characteristic data therein, select the experimental data under these key levels from all experimental simulations, and further screen the experimental data to screen out all characteristic data under the experimental data whose moving deviation values ​​are less than the moving deviation threshold;

[0089] The characteristic data of all experimental data screened out by all nonlinear characteristics are combined, and experimental simulation is performed again based on the screened characteristic data based on the orthogonal analysis method. If the gap nonlinear characteristics, friction nonlinear characteristics, elastic deformation nonlinear characteristics, dead zone nonlinear characteristics and saturation nonlinear characteristics are selected respectively , , , , group data, then a total of Experimental simulations are performed; the experimental data with the smallest movement deviation value is selected from the results of these experimental simulations, and the various components and parameters in the electromechanical servo system are adjusted according to the characteristic data in this set of experimental data.

[0090] By finely dividing the characteristic data levels and using the orthogonal analysis method for multiple rounds of experimental simulations, the key characteristic data and their optimal levels were effectively identified; not only the operating accuracy of the servo motor was significantly improved, but also the superiority of the final characteristic data group was ensured through layer-by-layer screening and optimization, providing a scientific basis for the precise adjustment of the electromechanical servo system; the control strategy based on orthogonal characteristics greatly enhanced the system's control ability over nonlinear characteristics and achieved performance optimization.

[0091] refer to Figure 3 The present invention also provides an electromechanical servo nonlinear control system based on orthogonal characteristics, comprising:

[0092] The data acquisition module performs three-dimensional modeling on the electromechanical servo system; obtains the nonlinear characteristics of the electromechanical servo system and obtains the key parameters under each nonlinear characteristic;

[0093] The characteristic data determination module establishes a nonlinear characteristic set, each of which contains a corresponding characteristic data set; obtains multiple sets of characteristic data during normal operation and abnormal operation from historical operation data, and obtains a standard value range for each characteristic data; selects characteristic values ​​for each characteristic data, and forms a corresponding characteristic data set;

[0094] The key feature identification module assigns different levels to the data in each feature data set; performs multiple experimental simulations of multiple sets of feature data at different levels based on the orthogonal analysis method, calculates the range of each feature data based on the obtained moving deviation value, and identifies the key levels under the key feature data; screens out the experimental data under these key levels, and screens out all experimental data with moving deviation values ​​less than the moving deviation threshold;

[0095] The comprehensive simulation control module combines all the experimental data screened out by nonlinear characteristics, performs experimental simulation again based on orthogonal analysis, screens out the final characteristic data set, and makes corresponding adjustments in the electromechanical servo system.

[0096] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer storage medium or transmitted via a computer storage medium.

[0097] Computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. Computer storage media can be any available media that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. Available media can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid state drives (SSDs)).

[0098] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for electromechanical servo nonlinear control based on orthogonal characteristics, characterized in that: include: 3D modeling of electromechanical servo systems; Obtain the nonlinear characteristics of the electromechanical servo system and obtain the key parameters under each nonlinear characteristic; Establishing a nonlinear feature set, each nonlinear feature set contains a corresponding feature data set; Acquire multiple sets of feature data during normal operation and abnormal operation from historical operation data, and obtain a standard value range for each feature data; select feature values ​​for each feature data and form a corresponding feature data set; Obtain the value range of each characteristic data when the servo motor is operating normally; obtain the value range of each characteristic data when the servo motor is operating abnormally, and determine that the cause of the abnormal operation is the abnormality of the corresponding characteristic data; combine the value range of each characteristic data when the servo motor is operating normally with the value range when the servo motor is operating abnormally to obtain the standard value range of each characteristic data; The method for determining the standard numerical range is specifically as follows: removing the numerical range corresponding to the intersection of the numerical range during normal operation and the numerical range during abnormal operation from the numerical range during normal operation of the servo motor, to obtain the standard numerical range of each characteristic data; If the value range of the characteristic data when the servo motor is not operating normally includes the value range when the servo motor is operating normally, it is necessary to divide the value range when the servo motor is not operating normally into blocks. If the difference between two adjacent values ​​exceeds a preset difference threshold, the value range when the servo motor is not operating normally is divided into two blocks, and the maximum value of the value range of the first part is the smaller value of the two values, and the minimum value of the value range of the second part is the larger value of the two values. Taking out each characteristic data in turn, setting other characteristic data according to standard values, and performing simulation in a three-dimensional model of the electromechanical servo system, wherein the standard value is the median value of the standard value range of each characteristic data; Starting from the minimum value in the standard numerical range of the selected characteristic data, the operation simulation of the servo motor is performed in sequence, and the movement deviation after simulation is obtained; based on the relationship between the movement deviation after simulation and the movement deviation threshold, the standard numerical range is divided into two or three parts; the numerical range in which the movement deviation after simulation does not exceed the movement deviation threshold is recorded as the first numerical range, and the numerical range in which the movement deviation after simulation exceeds the movement deviation threshold is recorded as the second numerical range; The median value of each feature data within the first numerical range and the second numerical range is used to form a data set of corresponding feature data according to the size of the data, that is, each feature data set in the nonlinear characteristic set; Assign different levels to the data in each feature data set; perform multiple experimental simulations of feature data at different levels based on the orthogonal analysis method, calculate the range of each feature data based on the obtained moving deviation value, and identify the key levels under the key feature data; filter out the experimental data at the key level, and filter out all experimental data with moving deviation values ​​less than the moving deviation threshold; All experimental data screened out by nonlinear characteristics are combined, and experimental simulation is performed again based on the orthogonal analysis method to screen out the final characteristic data group, and corresponding adjustments are made in the electromechanical servo system.

2. The electromechanical servo nonlinear control method based on orthogonal characteristics according to claim 1, characterized in that: The nonlinear characteristics obtained include gap nonlinear characteristics, friction nonlinear characteristics, elastic deformation nonlinear characteristics, dead zone nonlinear characteristics and saturation nonlinear characteristics; The key parameters of the gap nonlinear characteristics are transmission clearance and preload; the key parameters of the friction nonlinear characteristics are friction coefficient and lubrication index; the key parameters of the elastic deformation nonlinear characteristics are elastic modulus and coupling stiffness; the key parameters of the dead zone nonlinear characteristics are sensor sensitivity and actuator resolution; the key parameters of the saturation nonlinear characteristics are power amplifier gain and control algorithm parameters.

3. The electromechanical servo nonlinear control method based on orthogonal characteristics as claimed in claim 2, characterized in that: The lubrication index Li is determined based on the lubricant dosage Lu, the coverage area percentage Pac on the friction surface, and the replacement cycle Rc on each sliding surface, rolling bearing in the transmission mechanism, and the rotor and stator surfaces in the servo motor. The expression is: Li = α1*Lu+α2*Pac+α3*Rc, where α1, α2, and α3 represent the preset proportional coefficients of the lubricant dosage Lu, the coverage area percentage Pac on the friction surface, and the replacement cycle Rc, respectively.

4. The electromechanical servo nonlinear control method based on orthogonal characteristics as claimed in claim 3, characterized in that: The gap nonlinear characteristic set is TC i represents the transmission clearance dataset between the i-th gear or bearing, PL i represents the preload data set of the i-th gear or bearing, n1 represents the adjacent gears or adjacent bearings, or the total number of adjacent gears and bearings, and n2 represents the total number of gears and bearings; the transmission clearance data set and the preload data set are the characteristic data sets of the clearance nonlinear characteristics; The friction nonlinear characteristic set is CF i represents the friction coefficient dataset at the i-th friction surface, LI i represents the lubrication index data set at the i-th friction surface, n3 represents the total number of sliding surfaces, rolling bearing surfaces in the transmission mechanism, and the friction surfaces of the rotor and stator in the servo motor; the friction coefficient data set and the lubrication index data set are the characteristic data sets of the friction nonlinear characteristics; The nonlinear characteristic set of elastic deformation is Among them, EM i represents the elastic modulus data set of the i-th coupling, CS i represents the coupling stiffness data set of the i-th coupling, and n4 represents the total number of couplings; the elastic modulus data set and the coupling stiffness data set are the characteristic data sets of the nonlinear characteristics of elastic deformation; The dead zone nonlinear characteristic set is Among them, SS i represents the sensitivity dataset of the i-th sensor, AR i represents the resolution data set of the i-th actuator, n5 represents the total number of sensors, and n6 represents the total number of actuators; the sensitivity data set and the resolution data set are the characteristic data sets of the dead zone nonlinear characteristics; The saturation nonlinear characteristic set is {OV, OA, PG, IT, DT}, where OV represents the output voltage gain data set of the power amplifier, OA represents the output current gain data set of the power amplifier, PG represents the proportional gain data set, IT represents the integral time constant data set, and DT represents the differential time constant data set; the output voltage gain data set, the output current gain data set, the proportional gain data set, the integral time constant data set, and the differential time constant data set are the characteristic data sets of the saturation nonlinear characteristics.

5. The electromechanical servo nonlinear control method based on orthogonal characteristics as claimed in claim 4, characterized in that: Acquire multiple sets of normal operation characteristic data from the historical operation data of the electromechanical servo system, wherein the normal operation refers to the operation process when the movement deviation of the servo motor after executing the instruction is less than the preset movement deviation threshold, and the movement deviation is obtained based on the Euclidean distance between the actual position of the servo motor after the movement is completed in the global coordinate system and the target position that should be reached; Multiple sets of the above characteristic data during abnormal operation are obtained from the historical operation data of the electromechanical servo system. Abnormal operation refers to the operation process when the movement deviation of the servo motor after executing the instruction is not less than the preset movement deviation threshold.

6. The electromechanical servo nonlinear control method based on orthogonal characteristics according to claim 1, characterized in that: Obtain each feature data set in each type of nonlinear characteristic set in turn, assign a corresponding level to each data, and specifically record these data as small or low feature data, medium feature data, and large or high feature data according to their size; The experimental simulation is performed using the combination method of all characteristic data in the nonlinear characteristics at different levels; for the gap nonlinear characteristic set, if there are m characteristic data sets containing 2 data, then a total of The experimental simulation is performed, and the calculation method of the experimental times of the remaining nonlinear characteristic sets is the same; after each experimental simulation, the moving deviation value obtained by analysis is recorded; For each feature data set in the nonlinear characteristics, the moving deviation mean value at each level is calculated; the range of the moving deviation mean values ​​at all levels in each feature data set is calculated, that is, the difference between the maximum moving deviation mean value and the minimum moving deviation mean value under the feature data; The characteristic data with a range greater than a preset range threshold is regarded as the key characteristic data affecting the running accuracy of the servo motor; for each key characteristic data, the level with the smallest moving deviation average is recorded as the key level.

7. The electromechanical servo nonlinear control method based on orthogonal characteristics as claimed in claim 6, characterized in that: Obtain the key levels of all key characteristic data of each nonlinear characteristic, select the experimental data under these key levels from all experimental simulations, and screen out all characteristic data under the experimental data whose moving deviation values ​​are less than the moving deviation threshold; Combine all the characteristic data under the experimental data screened out for all nonlinear characteristics, and perform experimental simulation based on the screened characteristic data. If m1, m2, m3, m4, and m5 groups of data are selected for the gap nonlinear characteristic, friction nonlinear characteristic, elastic deformation nonlinear characteristic, dead zone nonlinear characteristic, and saturation nonlinear characteristic, then a total of m1*m2*m3*m4*m5 experimental simulations are required; select the experimental data with the smallest movement deviation value from the results of these experimental simulations, and adjust each component and parameter in the electromechanical servo system according to the characteristic data in this group of experimental data.

8. An electromechanical servo nonlinear control system based on orthogonal characteristics, characterized in that: include: Data acquisition module, which performs three-dimensional modeling of the electromechanical servo system; Obtain the nonlinear characteristics of the electromechanical servo system and obtain the key parameters under each nonlinear characteristic; A feature data determination module is used to establish a nonlinear feature set, each of which contains a corresponding feature data set; Acquire multiple sets of feature data during normal operation and abnormal operation from historical operation data, and obtain a standard value range for each feature data; select feature values ​​for each feature data and form a corresponding feature data set; Obtain the value range of each characteristic data when the servo motor is operating normally; obtain the value range of each characteristic data when the servo motor is operating abnormally, and determine that the cause of the abnormal operation is the abnormality of the corresponding characteristic data; combine the value range of each characteristic data when the servo motor is operating normally with the value range when the servo motor is operating abnormally to obtain the standard value range of each characteristic data; The method for determining the standard numerical range is specifically as follows: removing the numerical range corresponding to the intersection of the numerical range during normal operation and the numerical range during abnormal operation from the numerical range during normal operation of the servo motor, to obtain the standard numerical range of each characteristic data; If the value range of the characteristic data when the servo motor is not operating normally includes the value range when the servo motor is operating normally, it is necessary to divide the value range when the servo motor is not operating normally into blocks. If the difference between two adjacent values ​​exceeds a preset difference threshold, the value range when the servo motor is not operating normally is divided into two blocks, and the maximum value of the value range of the first part is the smaller value of the two values, and the minimum value of the value range of the second part is the larger value of the two values. Taking out each characteristic data in turn, setting other characteristic data according to standard values, and performing simulation in a three-dimensional model of the electromechanical servo system, wherein the standard value is the median value of the standard value range of each characteristic data; Starting from the minimum value in the standard numerical range of the selected characteristic data, the operation simulation of the servo motor is performed in sequence, and the movement deviation after simulation is obtained; the standard numerical range is divided into two or three parts based on the relationship between the movement deviation after simulation and the movement deviation threshold; the numerical range in which the movement deviation after simulation does not exceed the movement deviation threshold is recorded as the first numerical range, and the numerical range in which the movement deviation after simulation exceeds the movement deviation threshold is recorded as the second numerical range; The median value of each feature data within the first numerical range and the second numerical range is used to form a data set of corresponding feature data according to the size of the data, that is, each feature data set in the nonlinear characteristic set; The key feature identification module assigns different levels to the data in each feature data set; performs multiple experimental simulations of multiple sets of feature data at different levels based on the orthogonal analysis method, calculates the range of each feature data based on the obtained moving deviation value, and identifies the key levels under the key feature data; screens out the experimental data under these key levels, and screens out all experimental data with moving deviation values ​​less than the moving deviation threshold; The comprehensive simulation control module combines all the experimental data screened out by nonlinear characteristics, performs experimental simulation again based on orthogonal analysis, screens out the final characteristic data set, and makes corresponding adjustments in the electromechanical servo system.

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