An adaptive control method and apparatus for an ac servo system

Abstract

The embodiment of the application provides a kind of adaptive control method and device for AC servo system, the method comprises: obtaining the original state information variable and sampling period variable of the AC servo system;Based on the original state information variable, scaling transformation is carried out, to obtain new state information variable, wherein the new state information variable includes adaptive parameter variable;Based on the preset supervision function and the preset adaptive switching law, the adaptive parameter variable and the sampling period variable are adjusted, to obtain target adaptive parameter and target sampling period;Based on the target adaptive parameter and the target sampling period, the AC servo system is controlled, to realize adaptive control to AC servo system, to ensure that the adaptive adjustment of sampling period is realized in digital servo system, while maintaining effective processing to system uncertainty factor.

Description

Technical Field

[0001] This application relates to the field of AC servo system control technology, and in particular to an adaptive control method and apparatus for AC servo systems. Background Technology

[0002] In modern control theory, adaptive control methods are widely used in various complex control systems, especially servo systems, due to their significant advantages in handling system uncertainties. Servo systems typically need to maintain high performance in the face of uncertainties such as parameter variations, external disturbances, and changes in the system's internal structure. Adaptive control, by adjusting controller parameters in real time, can effectively cope with these uncertainties, thereby ensuring the stability and performance of the system.

[0003] However, the introduction of digital controllers and system sampling introduces the influence of the sampling period on the system's dynamic characteristics. While adaptive adjustment of controller parameters is relatively mature in traditional adaptive control methods, there is currently no effective adaptive adjustment strategy for the sampling period, a crucial parameter in digital control. This is particularly challenging when dealing with completely unknown or highly variable parameters, making sampling period adjustment extremely difficult. This limitation restricts the application of adaptive control in digital servo systems, especially in applications requiring precise control and efficient energy utilization. Therefore, achieving adaptive sampling period adjustment in digital servo systems while effectively handling system uncertainties has become a pressing issue in the field of control. Summary of the Invention

[0004] The main objective of this application is to propose an adaptive control method and apparatus for AC servo systems, which aims to achieve adaptive control of AC servo systems to ensure adaptive adjustment of the sampling period in digital servo systems while maintaining effective handling of system uncertainties.

[0005] To achieve the above objectives, a first aspect of this application proposes an adaptive control method for an AC servo system, the method comprising:

[0006] Obtain the original state information variables and sampling period variables of the AC servo system;

[0007] Based on the original state information variables, a scaling transformation is performed to obtain new state information variables, wherein the new state information variables include adaptive parameter variables;

[0008] The adaptive parameter variable and the sampling period variable are adjusted based on a preset supervision function and a preset adaptive switching law to obtain the target adaptive parameter and the target sampling period.

[0009] The AC servo system is controlled based on the target adaptive parameters and the target sampling period.

[0010] The method provided in the first aspect enables dynamic adjustment of the sampling period of the AC servo system in a digital environment, effectively addressing system uncertainties and avoiding instability or excessive energy consumption caused by excessively large or small sampling periods, thereby significantly improving the overall performance and reliability of the system. Simultaneously, the adaptive control mechanism can monitor and automatically adjust the control strategy in real time to address uncertainties such as load fluctuations, parameter changes, and external interference, ensuring stable operation under complex conditions and significantly improving the system's robustness and adaptability.

[0011] In one possible implementation, the supervision function is determined through the following steps:

[0012] Two consecutive sampling time points are obtained, including a first sampling time point and a second sampling time point, wherein the difference between the first sampling time point and the second sampling time point is the sampling period variable;

[0013] The supervision function is calculated based on the first sampling time point, the second sampling time point, the new state information, and the preset Lyapunov function.

[0014] In one possible implementation, adjusting the adaptive parameter variable and the sampling period variable based on a preset supervision function to obtain the target adaptive parameter and the target sampling period includes:

[0015] Read the value of the preset supervision function;

[0016] When the value of the supervision function is less than or equal to 0, the adaptive parameter variable and the sampling period variable are not updated, and the current adaptive parameter and the current sampling period are used as the target adaptive parameter and the target sampling period.

[0017] When the value of the supervision function is greater than 0, the adaptive parameter variable and the sampling period variable are adjusted based on the adaptive switching law to obtain the target adaptive parameter and the target sampling period.

[0018] In one possible implementation, when the value of the supervision function is greater than 0, adjusting the adaptive parameter variable and the sampling period variable based on the adaptive switching law to obtain the target adaptive parameter and the target sampling period includes:

[0019] The signal variable is calculated based on the value of the supervision function to obtain the target signal value;

[0020] The value of the adaptive parameter variable is calculated based on the preset first adaptive switching law and the target signal value to obtain the target adaptive parameter;

[0021] The target sampling period is determined based on the target adaptive parameters;

[0022] The formula for the first adaptive switching law is as follows:

[0023] , ,

[0024] in, This represents the adaptive parameter variable. This represents the preset first design parameter. Represents signal variables.

[0025] In one possible implementation, determining the target sampling period based on the target adaptive parameters includes:

[0026] Based on the target adaptive parameters, determine whether the second adaptive switching law holds true;

[0027] If true, then the sampling period variable will not be updated, and the current sampling period will be used as the target sampling period;

[0028] If not, the value of the sampling period variable is adjusted to make the second adaptive switching law valid, and the adjusted sampling period is taken as the target sampling period.

[0029] The formula for the second adaptive switching law is as follows:

[0030] , ,

[0031] in, This represents the adaptive parameter variable. This represents the sampling period variable. This indicates the preset second design parameter.

[0032] In one possible implementation, calculating the signal variable based on the value of the supervision function to obtain the target signal value includes:

[0033] Obtain the sampling sequence number of two consecutive sampling time points;

[0034] Read the value of the sampling sequence number;

[0035] When the value of the sampling sequence number is equal to 0, the target signal value is determined based on the first design parameters;

[0036] When the value of the sampling sequence number is greater than or equal to 1, the target signal value is determined based on the value of the supervision function.

[0037] In one possible implementation, determining the target signal value based on the first design parameter when the value of the sampling sequence number is equal to 0 includes:

[0038] When the value of the sampling sequence number is equal to 0, a normal number is selected as the target signal value so that the product of the first design parameter and the target signal value is greater than or equal to 1.

[0039] The step of determining the target signal value based on the value of the supervision function when the value of the sampling sequence number is greater than or equal to 1 includes:

[0040] When the value of the sampling sequence number is greater than or equal to 1, it is determined whether the value of the supervision function is greater than 0. If it is, 1 is added to the current signal value to obtain the target signal value. If not, the signal value is not updated, and the current signal value is used as the target signal value.

[0041] To achieve the above objectives, a second aspect of this application provides an adaptive control device for an AC servo system, the device comprising:

[0042] Variable acquisition module: used to acquire the original state information variables and sampling period variables of the AC servo system;

[0043] Scaling module: used to perform scaling transformation based on the original state information variables to obtain new state information variables, wherein the new state information variables include adaptive parameter variables;

[0044] Adaptive adjustment module: used to adjust the adaptive parameter variable and the sampling period variable based on a preset supervision function and a preset adaptive switching law to obtain the target adaptive parameter and the target sampling period;

[0045] Control module: Used to control the AC servo system based on the target adaptive parameters and the target sampling period.

[0046] The device provided in the second aspect enables dynamic adjustment of the sampling period of the AC servo system in a digital environment, effectively addressing system uncertainties and preventing instability or excessive energy consumption caused by excessively large or small sampling periods, thereby significantly improving the overall performance and reliability of the system. Simultaneously, the adaptive control mechanism can monitor and automatically adjust the control strategy in real time to address uncertainties such as load fluctuations, parameter changes, and external interference, ensuring stable operation of the system under complex conditions and significantly improving its robustness and adaptability.

[0047] Thirdly, an electronic device is provided, the electronic device including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the adaptive control method for an AC servo system as described in any possible implementation of the first aspect.

[0048] Fourthly, a computer-readable storage medium is provided, the storage medium storing a computer program that, when executed by a processor, implements the adaptive control method for an AC servo system as described in any possible implementation of the first aspect. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in one or more embodiments or prior art of this specification, the accompanying drawings used in the description of one or more embodiments or prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart illustrating the adaptive control method for an AC servo system provided in an embodiment of this application.

[0051] Figure 2 This is a schematic diagram of the state changes of the AC servo system provided in this application embodiment after adaptive control;

[0052] Figure 3 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0053] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described one or more embodiments are merely some embodiments of this specification, and not all embodiments. All other embodiments obtained by those skilled in the art based on one or more embodiments of this specification without creative effort should fall within the protection scope of this document.

[0054] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0056] Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other. The embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0057] Figure 1 This is an optional flowchart of the adaptive control method for an AC servo system provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S100 to S400.

[0058] To achieve the above objectives, a first aspect of this application proposes an adaptive control method for an AC servo system, the method comprising:

[0059] S100: Obtain the original state information variables and sampling period variables of the AC servo system.

[0060] It should be noted that the model of an AC servo system can be established in the following form:

[0061] ,

[0062] ,

[0063] ,

[0064] in, , representing the raw state information variables of the servo system, such as position, speed, current, etc., here The value can be any positive integer. Therefore, the model order of the AC servo system provided in this application is not limited to first or second order, but can be higher order. The adaptive control method for AC servo systems provided in this application can adapt to servo systems with very high model order, such as flexible robotic arms and humanoid robots. This allows for a more accurate description of the complex dynamic characteristics inside the AC servo system. When facing complex working conditions and high-precision control requirements, it can predict and respond more accurately, thereby significantly improving control accuracy and greatly expanding its application scenarios.

[0065] It should be noted that, This represents the nonlinear factors present in the servo system, satisfying... ,in This represents an unknown variable, a normal number, and an uncertainty factor in the servo system. The adaptive control method for AC servo systems provided in this application can handle such uncertainties, ensuring that the system can still operate stably under complex working conditions, and significantly improving the robustness and adaptability of the system.

[0066] S200. Based on the original state information variables, a scaling transformation is performed to obtain new state information variables, which include adaptive parameter variables.

[0067] It should be noted that in order to obtain the adaptive parameter variables, a scaling transformation is required based on the original state information variables. This scaling transformation is also known as coordinate transformation. After scaling the original state information variables, new state information variables can be obtained, and thus the adaptive parameter variables in the obtained state information variables can be adjusted subsequently. This enables the adaptive control method for AC servo systems provided in this application to handle uncertainties in AC servo systems and ensure that the system can still operate stably under complex working conditions.

[0068] S300: Based on a preset supervision function and a preset adaptive switching law, the adaptive parameter variable and the sampling period variable are adjusted to obtain the target adaptive parameter and the target sampling period.

[0069] It should be noted that, due to the sampling conditions of digital controllers or systems, traditional adaptive control methods struggle to handle uncertainties in servo systems, especially when uncertain parameters are completely unknown or have a large range of variation. Furthermore, the sampling period is a crucial element in digital control systems, connecting continuous-time and discrete-time signals, and its magnitude directly impacts system performance. If the sampling period is too large, the system cannot capture dynamic changes in a timely manner, leading to a lag in control signal updates and potentially causing system instability. This instability can severely affect normal system operation, particularly in applications requiring rapid dynamic response and high-precision control. Conversely, a sampling period that is too small, while improving response speed, can lead to oversampling, increasing computational burden and energy consumption. This is extremely detrimental to servo systems requiring long-term stable operation, reducing energy efficiency and potentially impacting reliability and lifespan due to excessive energy consumption. Therefore, this application proposes to dynamically adjust the adaptive parameter variable and sampling period variable based on the value of the preset supervision function by using a preset adaptive switching law, so as to select appropriate adaptive parameters and sampling period. This enables the system to flexibly cope with uncertainties, and to appropriately reduce the sampling period to improve response speed and control accuracy when the system changes rapidly or the accuracy requirements are high, or to moderately increase the sampling period to reduce energy consumption and computational burden when the system is running smoothly or the load is light, thus significantly improving the robustness and adaptability of the system.

[0070] S400 controls the AC servo system based on target adaptive parameters and target sampling period.

[0071] The method provided in the first aspect enables dynamic adjustment of the sampling period of the AC servo system in a digital environment, effectively addressing system uncertainties and avoiding instability or excessive energy consumption caused by excessively large or small sampling periods, thereby significantly improving the overall performance and reliability of the system. Simultaneously, the adaptive control mechanism can monitor and automatically adjust the control strategy in real time to address uncertainties such as load fluctuations, parameter changes, and external interference, ensuring stable operation under complex conditions and significantly improving the system's robustness and adaptability.

[0072] In one possible implementation, the supervision function is determined through the following steps: obtaining two consecutive sampling time points, including a first sampling time point and a second sampling time point, wherein the difference between the first sampling time point and the second sampling time point is the sampling period variable; and calculating the supervision function based on the first sampling time point, the second sampling time point, the new state information, and a preset Lyapunov function.

[0073] It should be noted that, in order to determine the value of the supervision function, two consecutive sampling time points are required, including the first sampling time point and the second sampling time point. The difference between the first sampling time point and the second sampling time point is the sampling period variable. Then, the supervision function is calculated based on the first sampling time point, the second sampling time point, the new state information, and the preset Lyapunov function. The specific formula is as follows:

[0074] ,

[0075] in, Represents the supervision function, This represents the pre-defined Lyapunov function. This indicates new status information. Indicates the first sampling time point. Indicates the second sampling time point. This represents a positive constant greater than 0, obtained from the AC servo system.

[0076] It should also be noted that the specific formula for the Lyapunov function is as follows:

[0077] ,

[0078] in, This represents the pre-defined Lyapunov function. This indicates new status information. satisfy as well as ,and , The specific formula is as follows:

[0079] ,

[0080] The Lyapunov function is a scalar function used in stability studies of nonlinear and complex dynamic systems to determine the stability characteristics of a system near its equilibrium point. Calculating the value of the monitoring function using the Lyapunov function is beneficial for subsequent adjustments to adaptive parameter variables and sampling period variables, thereby improving the robustness and adaptability of the system.

[0081] In one possible implementation, adjusting the adaptive parameter variable and the sampling period variable based on a preset supervision function to obtain the target adaptive parameter and the target sampling period includes: reading the value of the preset supervision function; when the value of the supervision function is less than or equal to 0, not updating the adaptive parameter variable and the sampling period variable, and using the current adaptive parameter and the current sampling period as the target adaptive parameter and the target sampling period; when the value of the supervision function is greater than 0, adjusting the adaptive parameter variable and the sampling period variable based on the adaptive switching law to obtain the target adaptive parameter and the target sampling period.

[0082] It should be noted that due to uncertainties in the servo system, the selection of adaptive parameter variables and sampling period variables is difficult. Therefore, a preset supervision function is needed to adjust the adaptive parameter variables and sampling period variables. Specifically, the value of the supervision function needs to be determined through the following steps: Two consecutive sampling time points are obtained, including a first sampling time point and a second sampling time point, where the difference between the first and second sampling time points is the sampling period variable; the supervision function is calculated based on the first sampling time point, the second sampling time point, new state information, and a preset Lyapunov function. After obtaining the value of the supervision function, if the value of the supervision function is less than or equal to 0, the adaptive parameter variables and sampling period variables are not updated, and the current adaptive parameters and the current sampling period are used as the target adaptive parameters and the target sampling period. If the value of the supervision function is greater than 0, the adaptive parameter variables and sampling period variables are adjusted based on the adaptive switching law to obtain the target adaptive parameters and the target sampling period.

[0083] In one possible implementation, when the value of the supervision function is greater than 0, adjusting the adaptive parameter variable and the sampling period variable based on the adaptive switching law to obtain the target adaptive parameter and the target sampling period includes: calculating a signal variable based on the value of the supervision function to obtain a target signal value; calculating the value of the adaptive parameter variable according to a preset first adaptive switching law and the target signal value to obtain the target adaptive parameter; and determining the target sampling period based on the target adaptive parameter. The formula for the first adaptive switching law is as follows:

[0084] , ,

[0085] in, This represents the adaptive parameter variable. This represents the preset first design parameter. Represents signal variables.

[0086] It should be noted that due to uncertainties in the servo system, the selection of adaptive parameter variables and sampling period variables is difficult. Therefore, a preset supervision function is needed to adjust the adaptive parameter variables and sampling period variables. Specifically, the value of the supervision function needs to be determined through the following steps: Two consecutive sampling time points are obtained, including a first sampling time point and a second sampling time point, where the difference between the first and second sampling time points is the sampling period variable; the supervision function is calculated based on the first sampling time point, the second sampling time point, new state information, and a preset Lyapunov function. After obtaining the value of the supervision function, when the value of the supervision function is greater than 0, the signal variable is calculated based on the value of the supervision function to obtain the target signal value. Then, the value of the adaptive parameter variable is calculated according to the preset first adaptive switching law and the target signal value to obtain the target adaptive parameter. Finally, the target sampling period is determined based on the target adaptive parameter. The formula for the first adaptive switching law is as follows:

[0087] , ,

[0088] in, This represents the adaptive parameter variable. This represents the preset first design parameter. The signal variable is represented by the first design parameter, which is a normal number. The first adaptive switching law is used to continuously increase the value of the adaptive parameter variable, thereby increasing the control gain of the servo system and improving the stability of the entire control system.

[0089] In one possible implementation, determining the target sampling period based on the target adaptive parameter includes: determining whether a second adaptive switching law holds true based on the target adaptive parameter; if true, not updating the sampling period variable and using the current sampling period as the target sampling period; if false, adjusting the value of the sampling period variable to make the second adaptive switching law hold true, and using the adjusted sampling period as the target sampling period; the formula for the second adaptive switching law is as follows:

[0090] , ,

[0091] in, This represents the adaptive parameter variable. This represents the sampling period variable. This indicates the preset second design parameter.

[0092] It should be noted that in some embodiments, the sampling period is a crucial link connecting continuous-time signals and discrete-time signals in a digital control system, and its magnitude directly affects the system's performance. If the sampling period is too large, the system cannot capture dynamic changes in time, leading to a lag in the update of control signals, which may cause system instability. This instability can severely affect the normal operation of the system, especially in situations requiring rapid dynamic response and high-precision control. Conversely, if the sampling period is too small, although it can improve the system's response speed, it will lead to oversampling, increasing the system's computational burden and energy consumption. This is extremely detrimental to servo systems that require long-term stable operation, as it will not only reduce the system's energy efficiency but may also affect the system's reliability and lifespan due to excessive energy consumption. Therefore, it is necessary to determine the target sampling period based on the target adaptive parameters. Specifically, based on the target adaptive parameters, it is determined whether the second adaptive switching law holds. If it holds, the sampling period variable is not updated, and the current sampling period is taken as the target sampling period. If it does not hold, the value of the sampling period variable is adjusted to make the second adaptive switching law hold, and the adjusted sampling period is taken as the target sampling period. The formula for the second adaptive switching law is as follows:

[0093] , ,

[0094] in, Indicates adaptive parameter variables, Indicates the sampling period variable. This represents the preset second design parameter, which is a normal number. The second adaptive switching law is used to prevent the value of the sampling period variable from becoming too large, thus avoiding overall system instability.

[0095] In one possible implementation, calculating the signal variable based on the value of the supervision function to obtain the target signal value includes: obtaining the sampling sequence number of two consecutive sampling time points; reading the value of the sampling sequence number; when the value of the sampling sequence number is equal to 0, determining the target signal value based on the first design parameter; when the value of the sampling sequence number is greater than or equal to 1, determining the target signal value based on the value of the supervision function.

[0096] It should be noted that in order to obtain the target signal value and determine the target adaptive parameters, it is necessary to perform calculations based on the value of the supervision function. Specifically, the sampling sequence number of two consecutive sampling time points is obtained and the value of the sampling sequence number is read. When the value of the sampling sequence number is equal to 0, the target signal value is determined based on the first design parameter. When the value of the sampling sequence number is greater than or equal to 1, the target signal value is determined based on the supervision function.

[0097] In one possible implementation, determining the target signal value based on the first design parameter when the value of the sampling number is equal to 0 includes: when the value of the sampling number is equal to 0, selecting a positive integer as the target signal value, such that the product of the first design parameter and the target signal value is greater than or equal to 1; determining the target signal value based on the value of the supervision function when the value of the sampling number is greater than or equal to 1 includes: when the value of the sampling number is greater than or equal to 1, determining whether the value of the supervision function is greater than 0; if so, adding 1 to the current signal value to obtain the target signal value; if not, not updating the signal value and using the current signal value as the target signal value.

[0098] It should be noted that when the sampling sequence number is equal to 0, the target signal value is determined based on the first design parameter. Specifically, the target signal value is selected as a positive constant, such that... If the value is greater than or equal to 1, the target signal value is determined based on the supervision function. Specifically, it is determined whether the value of the supervision function is greater than 0. If so, 1 is added to the current signal value to obtain the target signal value. If not, the signal value is not updated, and the current signal value is used as the target signal value. The specific formula is as follows:

[0099] ,

[0100] in, Indicates the sampling sequence number. Indicates the target signal value. This represents the supervisory function.

[0101] In some embodiments, a verification method is also provided for verifying the stability of an AC servo system after controlling it based on target adaptive parameters and a target sampling period. Specifically, this includes: First, by giving a finite number of samplings, proving that the amplitudes of all signals over the sampling period are bounded, i.e., their magnitudes will not exceed a certain range, indicating that the system will not experience infinite signal amplitude growth or drastic fluctuations during sampling; Second, by contradiction, assuming the servo system will switch modes an infinite number of times, if this assumption is not true, then proving that the number of switching operations by the servo system controller is finite; Finally, based on the conclusion that the amplitudes of all signals over the sampling period are bounded and the number of switching operations by the servo system controller is finite, proving that all states of the AC servo system converge to 0 exponentially, thus proving that the AC servo system has stability and reliability. Figure 2 As shown, Figure 2 The states are shown respectively. controller Adaptive parameter variables Sampling period variable The changing trend, specifically, the state After a period of time, the convergence to 0 proves that the AC servo system has stability and reliability, and that it adapts to parameter variables. and sampling period variable By becoming sufficiently large and sufficiently small respectively, the stability of the closed-loop system is guaranteed.

[0102] To achieve the above objectives, a second aspect of this application provides an adaptive control device for an AC servo system, the device comprising:

[0103] Variable acquisition module: used to acquire the original state information variables and sampling period variables of the AC servo system.

[0104] Scaling module: used to perform scaling transformation based on the original state information variables to obtain new state information variables, wherein the new state information variables include adaptive parameter variables.

[0105] It should be noted that in order to obtain the adaptive parameter variables, a scaling transformation is required based on the original state information variables. This scaling transformation is also known as coordinate transformation. After scaling the original state information variables, new state information variables can be obtained, and thus the adaptive parameter variables in the obtained state information variables can be adjusted subsequently. This enables the adaptive control method for AC servo systems provided in this application to handle uncertainties in AC servo systems and ensure that the system can still operate stably under complex working conditions.

[0106] Adaptive adjustment module: used to adjust the adaptive parameter variable and the sampling period variable based on a preset supervision function and a preset adaptive switching law to obtain the target adaptive parameter and the target sampling period.

[0107] It should be noted that, due to the sampling conditions of digital controllers or systems, traditional adaptive control methods struggle to handle uncertainties in servo systems, especially when uncertain parameters are completely unknown or have a large range of variation. Furthermore, the sampling period is a crucial element in digital control systems, connecting continuous-time and discrete-time signals, and its magnitude directly impacts system performance. If the sampling period is too large, the system cannot capture dynamic changes in a timely manner, leading to a lag in control signal updates and potentially causing system instability. This instability can severely affect normal system operation, particularly in applications requiring rapid dynamic response and high-precision control. Conversely, a sampling period that is too small, while improving response speed, can lead to oversampling, increasing computational burden and energy consumption. This is extremely detrimental to servo systems requiring long-term stable operation, reducing energy efficiency and potentially impacting reliability and lifespan due to excessive energy consumption. Therefore, this application proposes to dynamically adjust the adaptive parameter variable and sampling period variable based on the value of the preset supervision function by using a preset adaptive switching law, so as to select appropriate adaptive parameters and sampling period. This enables the system to flexibly cope with uncertainties, and to appropriately reduce the sampling period to improve response speed and control accuracy when the system changes rapidly or the accuracy requirements are high, or to moderately increase the sampling period to reduce energy consumption and computational burden when the system is running smoothly or the load is light, thus significantly improving the robustness and adaptability of the system.

[0108] Control module: Used to control the AC servo system based on the target adaptive parameters and the target sampling period.

[0109] The device provided in the second aspect enables dynamic adjustment of the sampling period of the AC servo system in a digital environment, effectively addressing system uncertainties and preventing instability or excessive energy consumption caused by excessively large or small sampling periods, thereby significantly improving the overall performance and reliability of the system. Simultaneously, the adaptive control mechanism can monitor and automatically adjust the control strategy in real time to address uncertainties such as load fluctuations, parameter changes, and external interference, ensuring stable operation of the system under complex conditions and significantly improving its robustness and adaptability.

[0110] This application also provides an electronic device, such as... Figure 3 As shown, the electronic device 1400 includes:

[0111] One or more processors 1410;

[0112] The memory 1420 stores one or more programs that, when executed by one or more processors 1410, enable the one or more processors 1410 to implement the adaptive control method for an AC servo system provided in any embodiment of this application.

[0113] Memory 1420, as a non-transitory network system, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory 1420 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory 1420 may optionally include remotely located memories 1420 relative to processor 1410, which can be connected to processor 1410 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0114] The memory 1420 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1420 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1420 and is called and executed by the processor 1410.

[0115] The processor 1410 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0116] In some embodiments, the electronic device further includes:

[0117] Input / output interfaces are used to implement information input and output;

[0118] The communication interface is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0119] The bus transmits information between various components of the device (e.g., processor 1410, memory 1420, input / output interfaces, and communication interfaces);

[0120] The processor 1410, memory 1420, input / output interface, and communication interface can communicate with each other within the device via a bus.

[0121] An embodiment of this application also provides a computer-readable storage medium storing computer-executable instructions for executing an adaptive control method for an AC servo system provided in any embodiment of this application.

[0122] An embodiment of this application also provides a computer program product, including a computer program or computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer program or computer instructions from the computer-readable storage medium and executes the computer program or computer instructions, causing the computer device to perform an adaptive control method for an AC servo system provided in any embodiment of this application.

[0123] The system architecture and application scenarios described in this application are intended to more clearly illustrate the technical solutions of this application and do not constitute a limitation on the technical solutions provided in this application. Those skilled in the art will understand that as system architectures evolve and new application scenarios emerge, the technical solutions provided in this application are also applicable to similar technical problems.

[0124] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0125] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0126] The above description, with reference to the accompanying drawings, illustrates some embodiments of this application, but does not limit the scope of the invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and spirit of this invention should be considered within the scope of this application.

[0127] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0128] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0129] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0130] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0131] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0132] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. An adaptive control method for an AC servo system, characterized in that, The method includes: Obtain the original state information variables and sampling period variables of the AC servo system; Based on the original state information variables, a scaling transformation is performed to obtain new state information variables, wherein the new state information variables include adaptive parameter variables; Read the value of the preset supervision function; When the value of the supervision function is less than or equal to 0, the adaptive parameter variable and the sampling period variable are not updated, and the current adaptive parameter and the current sampling period are used as the target adaptive parameter and the target sampling period. When the value of the supervision function is greater than 0, the adaptive parameter variable and the sampling period variable are adjusted based on the adaptive switching law to obtain the target adaptive parameter and the target sampling period; The AC servo system is controlled based on the target adaptive parameters and the target sampling period; The supervision function is determined through the following steps: Two consecutive sampling time points are obtained, including a first sampling time point and a second sampling time point, wherein the difference between the first sampling time point and the second sampling time point is the sampling period variable; The supervision function is calculated based on the first sampling time point, the second sampling time point, the new state information, and the preset Lyapunov function.

2. The method according to claim 1, characterized in that, When the value of the supervision function is greater than 0, the adaptive parameter variable and the sampling period variable are adjusted based on the adaptive switching law to obtain the target adaptive parameter and the target sampling period, including: The signal variable is calculated based on the value of the supervision function to obtain the target signal value; The value of the adaptive parameter variable is calculated based on the preset first adaptive switching law and the target signal value to obtain the target adaptive parameter; The target sampling period is determined based on the target adaptive parameters; The formula for the first adaptive switching law is as follows: ，k=0，1......， in, This represents the adaptive parameter variable. This represents the preset first design parameter. Represents signal variables.

3. The method according to claim 2, characterized in that, Determining the target sampling period based on the target adaptive parameters includes: Based on the target adaptive parameters, determine whether the second adaptive switching law holds true; If true, then the sampling period variable will not be updated, and the current sampling period will be used as the target sampling period; If not, the value of the sampling period variable is adjusted to make the second adaptive switching law valid, and the adjusted sampling period is taken as the target sampling period. The formula for the second adaptive switching law is as follows: ，k=0，1......， in, This represents the adaptive parameter variable. This represents the sampling period variable. This indicates the preset second design parameter.

4. The method according to claim 3, characterized in that, The calculation of the signal variable based on the value of the supervision function to obtain the target signal value includes: Obtain the sampling sequence number of two consecutive sampling time points; Read the value of the sampling sequence number; When the value of the sampling sequence number is equal to 0, the target signal value is determined based on the first design parameters; When the value of the sampling sequence number is greater than or equal to 1, the target signal value is determined based on the value of the supervision function.

5. The method according to claim 4, characterized in that, When the value of the sampling sequence number is equal to 0, determining the target signal value based on the first design parameter includes: When the value of the sampling sequence number is equal to 0, a normal number is selected as the target signal value so that the product of the first design parameter and the target signal value is greater than or equal to 1. The step of determining the target signal value based on the value of the supervision function when the value of the sampling sequence number is greater than or equal to 1 includes: When the value of the sampling sequence number is greater than or equal to 1, it is determined whether the value of the supervision function is greater than 0. If it is, 1 is added to the current signal value to obtain the target signal value. If not, the signal value is not updated, and the current signal value is used as the target signal value.

6. An adaptive control device for an AC servo system, characterized in that, The device includes: Variable acquisition module: used to acquire the original state information variables and sampling period variables of the AC servo system; Scaling module: used to perform scaling transformation based on the original state information variables to obtain new state information variables, wherein the new state information variables include adaptive parameter variables; Adaptive adjustment module: used to read the value of a preset supervision function; when the value of the supervision function is less than or equal to 0, the adaptive parameter variable and the sampling period variable are not updated, and the current adaptive parameter and the current sampling period are used as the target adaptive parameter and the target sampling period; when the value of the supervision function is greater than 0, the adaptive parameter variable and the sampling period variable are adjusted based on the adaptive switching law to obtain the target adaptive parameter and the target sampling period; wherein, the supervision function is determined by the following steps: obtaining two consecutive sampling time points, including a first sampling time point and a second sampling time point, wherein the difference between the first sampling time point and the second sampling time point is the sampling period variable; calculating the supervision function based on the first sampling time point, the second sampling time point, the new state information and the preset Lyapunov function; Control module: Used to control the AC servo system based on the target adaptive parameters and the target sampling period.

7. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the adaptive control method for an AC servo system as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the adaptive control method for an AC servo system as described in any one of claims 1 to 5.

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