Sliding mode iteration control method and device of mechanical arm and electronic equipment

Abstract

The invention provides a sliding mode iteration control method and device for a mechanical arm and electronic equipment, and the method comprises the steps: constructing a mechanical arm dynamic model according to mechanical arm parameters, and adding the model uncertainty into the mechanical arm dynamic model; the model uncertainty comprises known disturbance and unknown disturbance; constructing a sliding mode surface based on the convergence rate and the singular characteristic; an equivalent control law and a switching control law are constructed, the equivalent control law is suitable for counteracting known disturbance, and the switching control law is suitable for counteracting unknown disturbance; generating a closed-loop iterative controller based on the trajectory deviation; determining a system control equation according to the closed-loop iteration controller, the equivalent control law and the switching control law; and the mechanical arm is controlled according to the system control equation, and a preset task is executed. According to the invention, iterative learning is carried out on the tracking error signal of the expected trajectory, so that high-precision tracking of the expected trajectory is realized on the basis of sliding mode control.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a sliding mode iterative control method, device and electronic equipment for a robotic arm. Background Art

[0002] Sliding Mode Control (SMC) is a nonlinear control strategy that is particularly suitable for uncertain systems and systems with external disturbances. It achieves the control goal of the system by forcing the system state to be constrained on a pre-designed sliding surface.

[0003] The sliding mode control of the robotic arm is characterized by strong robustness and high control accuracy; however, for medical robotic arms that require high-precision control, the tracking accuracy of the sliding mode control for the desired trajectory is still low. Summary of the invention

[0004] The problem solved by the present application is that the current sliding mode control of the robot arm has low tracking accuracy for the desired trajectory.

[0005] In order to solve the above problems, the first aspect of the present application provides a sliding mode iterative control method for a robot arm, comprising:

[0006] According to the parameters of the robot arm, a dynamic model of the robot arm is constructed, and model uncertainty is added to the dynamic model of the robot arm; the model uncertainty includes known disturbances and unknown disturbances;

[0007] Construct sliding surface based on convergence speed and singular characteristics;

[0008] Constructing an equivalent control law and a switching control law, wherein the equivalent control law is suitable for offsetting known disturbances, and the switching control law is suitable for offsetting unknown disturbances;

[0009] Based on the trajectory deviation, a closed-loop iterative controller is generated;

[0010] Determining a system control equation according to the closed-loop iterative controller, the equivalent control law and the switching control law;

[0011] The robot arm is controlled according to the system control equation to perform the preset task.

[0012] A second aspect of the present application provides a sliding mode iterative control device for a robotic arm, comprising:

[0013] A model building module, which is used to build a mechanical arm dynamics model according to the mechanical arm parameters, and add model uncertainty to the mechanical arm dynamics model; the model uncertainty includes known disturbances and unknown disturbances;

[0014] A sliding mode construction module, which is used to construct the sliding mode surface based on the convergence rate and singular characteristics;

[0015] A control law generation module, which is used to construct an equivalent control law and a switching control law, wherein the equivalent control law is suitable for offsetting known disturbances, and the switching control law is suitable for offsetting unknown disturbances;

[0016] A controller module, which is used to generate a closed-loop iterative controller based on the trajectory deviation;

[0017] An equation determination module, which is used to determine the system control equation according to the closed-loop iterative controller, the equivalent control law and the switching control law;

[0018] A robot arm control module is used to control the robot arm according to the system control equation to perform a preset task. A third aspect of the present application provides an electronic device, comprising: a memory and a processor;

[0019] The memory is used to store programs;

[0020] The processor, coupled to the memory, is configured to execute the program to:

[0021] According to the parameters of the robot arm, a dynamic model of the robot arm is constructed, and model uncertainty is added to the dynamic model of the robot arm; the model uncertainty includes known disturbances and unknown disturbances;

[0022] Construct sliding surface based on convergence speed and singular characteristics;

[0023] Constructing an equivalent control law and a switching control law, wherein the equivalent control law is suitable for offsetting known disturbances, and the switching control law is suitable for offsetting unknown disturbances;

[0024] Based on the trajectory deviation, a closed-loop iterative controller is generated;

[0025] Determining a system control equation according to the closed-loop iterative controller, the equivalent control law and the switching control law;

[0026] The robot arm is controlled according to the system control equation to perform the preset task.

[0027] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the program is executed by a processor to implement the above-mentioned sliding mode iterative control method for the robotic arm.

[0028] In the present application, by iteratively learning the tracking error signal of the desired trajectory, high-precision tracking of the desired trajectory is achieved based on sliding mode control. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1is a flow chart of a sliding mode iterative control method for a robotic arm according to an embodiment of the present application;

[0030] Figure 2 is a structural block diagram of a sliding mode iterative control device for a robotic arm according to an embodiment of the present application;

[0031] Figure 3 is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described in detail below in conjunction with the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0033] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the common meanings understood by technicians in the field to which this application belongs.

[0034] The present application embodiment provides a sliding mode iterative control method for a robotic arm, the specific scheme of the method is as follows: Figure 1-Figure 2 As shown, the method can be executed by a sliding mode iterative control device of a robot arm, and the sliding mode iterative control device of the robot arm can be integrated in electronic devices such as computers, servers, computers, server clusters, and data centers. Figure 1 As shown, it is a flow chart of a sliding mode iterative control method for a robotic arm according to an embodiment of the present application; wherein the sliding mode iterative control method for a robotic arm includes:

[0035] S101, constructing a mechanical arm dynamics model according to mechanical arm parameters, and adding model uncertainty to the mechanical arm dynamics model; the model uncertainty includes known disturbances and unknown disturbances;

[0036] Analyzing the robotic arm, it can be seen that the robotic arm is formed by connecting several rods (the place where two rods are connected is a joint), and these rods in the robotic arm are called connecting rods. Each connecting rod can rotate around a certain axis based on the husband connecting rod (the previous connecting rod) (the joint drives the connecting rod to rotate through the rotation of the motor), and this axis is only relative to the husband connecting rod. This results in that once multiple connecting rods are moving, the connecting rod can only have a direct spatial conversion relationship with the "previous level connecting rod" and the "next level connecting rod", that is, when the rotation angle of the first connecting rod is determined, the specific position of the first connecting rod can be calculated according to the spatial coordinates of the base, and then the position of the end robotic arm can be obtained by calculating backward one level at a time, which is the end position of the loading and unloading ratio.

[0037] In this application, known disturbances usually come from modeling errors, friction, etc.; unknown disturbances come from factors that are difficult to model (such as nonlinear friction, external random disturbances, etc.), and compensation methods are used in this application for estimation.

[0038] S102, constructing the sliding surface based on the convergence speed and singular characteristics;

[0039] Sliding mode is a form of motion that occurs and is maintained on the switching surface in a variable structure control system. Sliding mode is one of the main characteristics of a sliding mode variable structure control system.

[0040] The basic idea of ​​sliding mode variable structure control is to first divide the sliding mode motion of the system into two parts. The first part is the motion stage of the system from the initial state to the switching surface, which is called the arrival section; the second part is the motion stage of the system on the switching surface, namely the sliding mode section. Secondly, the design of the sliding mode controller is also divided into two parts. The first part is to design the mode surface of the sliding mode section according to the desired system dynamic characteristics to obtain satisfactory control performance; the second part is to design the arrival section of the sliding mode motion, usually according to the existence conditions of the sliding mode, to design the switching control so that the system state can enter the sliding mode surface designed in the first part under any initial conditions.

[0041] In this application, a suitable sliding surface function is selected to control the convergence speed of the error state.

[0042] In this application, it is necessary to avoid system instability caused by the singularity of certain parameters during the control process. When designing the sliding surface, the range of joint angular velocity and position changes must be fully considered to ensure that the sliding surface does not become singular in any state.

[0043] In one embodiment, the sliding surface is:

[0044]

[0045] Among them, α and β are normal coefficients, sign(*) is the sign function, r1 and r2 are constants, and 1 <r1<2,r1<r2。

[0046] S103, constructing an equivalent control law and a switching control law, wherein the equivalent control law is suitable for offsetting known disturbances, and the switching control law is suitable for offsetting unknown disturbances;

[0047] For the control process of the robot arm, there are parameter perturbations between model parameters, unknown disturbances, and known disturbances; the specific circumstances of parameter perturbations and disturbances cannot be fully known, and modeling analysis cannot be performed. In this application, the model parameter perturbations and the substitutions of unknown bounded disturbances and known disturbances are directly set to represent the overall disturbance of model parameter perturbations and unknown bounded disturbances and known disturbances, so that parameter perturbations and unknown disturbances and known disturbances can be solved / eliminated without analyzing and modeling the specific circumstances.

[0048] In this application, an equivalent control law is designed to offset known disturbances. The estimated disturbance information can be used to make the system reach a stable state without unknown disturbances.

[0049] In the present application, a switching control law is designed to offset unknown disturbances, for example, by using a sign function or a smooth function to approximate a sign function to improve control accuracy and disturbance resistance.

[0050] S104, generating a closed-loop iterative controller based on the trajectory deviation;

[0051] In this application, a closed-loop iterative controller is generated to adjust the control law in real time based on the deviation between the current trajectory and the target trajectory. Through successive iterations, the control input is updated according to the trajectory deviation information to ensure that the robot arm can stably track the target trajectory.

[0052] S105, determining a system control equation according to the closed-loop iterative controller, the equivalent control law and the switching control law;

[0053] In this application, the equivalent control law, the switching control law and the closed-loop iterative controller are combined into the final control equation.

[0054] S106, controlling the robot arm according to the system control equation to perform a preset task.

[0055] In this application, the control equations are applied to the actual control system of the robotic arm, and the joint torque is adjusted in real time to complete the preset task. The control input is continuously adjusted using feedback to ensure that the robotic arm can complete the specified task in a dynamic environment.

[0056] In the present application, by iteratively learning the tracking error signal of the desired trajectory, high-precision tracking of the desired trajectory is achieved based on sliding mode control.

[0057] In this application, the terminal sliding mode control realizes the effective suppression of disturbances and uncertain parameters of the robot system, ensuring the rapid convergence of the control error; the iterative learning controller continuously improves the tracking accuracy of the desired trajectory by gradually correcting the error.

[0058] In one embodiment, the dynamic equation of the robotic arm is:

[0059]

[0060] Where M(q) is the n×n dimensional positive definite inertia matrix, is the n×n dimensional centrifugal force and Coriolis force matrix, G(q) is the n×1 dimensional gravity term vector, the control input τ is the n×1 joint torque vector, n is the number of robot joints, q is the actual trajectory, is the time derivative of q, for The derivative with respect to time, τ d Represents an external unknown disturbance.

[0061] In one implementation, the equivalent control law is:

[0062]

[0063] Among them, τ eq is the equivalent control law, M0 is the positive definite inertia matrix of the nominal model, C0 is the centrifugal force and Coriolis force matrix of the nominal model, G0 is the gravity term vector of the nominal model, q is the actual trajectory, is the time derivative of q, for The derivative with respect to time, q d is the expected trajectory, and s is the sliding mode hyperplane.

[0064] In one implementation, the switching control law is:

[0065] τ sw =M0[ks+μsat(s)]

[0066] Among them, sat(s) is the saturation function, k and μ are the reaching law parameter matrices, M0 is the positive definite inertia matrix of the nominal model, and s is the sliding mode hyperplane.

[0067] In one implementation, the closed-loop iterative controller is:

[0068]

[0069] Among them, K d , K p is the positive definite gain parameter matrix, is the error equation, u k (t) is the controller output.

[0070] In one embodiment, the system control equation is:

[0071]

[0072] u k+1 (t) = u k (t)+Γ

[0073] Among them, Γ is the intermediate parameter, u k (t) is the controller output, M0 is the positive definite inertia matrix of the nominal model, C0 is the centrifugal force and Coriolis force matrix of the nominal model, and G0 is the gravity term vector of the nominal model.

[0074] In this application, terminal sliding mode control is used to achieve rapid convergence of the system to the sliding mode surface within a limited time, and the reaching law of the saturation function is used to enhance the anti-interference ability of the manipulator system and reduce the jitter of the system. An iterative learning controller is designed to iteratively learn the tracking error signal and update the control variable to achieve high-precision tracking of the desired trajectory and improve the performance of the system.

[0075] An embodiment of the present application provides a sliding mode iterative control device for a robotic arm, which is used to execute the sliding mode iterative control method for the robotic arm described in the above content of the present application. The sliding mode iterative control device for the robotic arm is described in detail below.

[0076] like Figure 2 As shown, the sliding mode iterative control device of the robot arm comprises:

[0077] A model building module 101 is used to build a mechanical arm dynamics model according to mechanical arm parameters, and add model uncertainty to the mechanical arm dynamics model; the model uncertainty includes known disturbances and unknown disturbances;

[0078] A sliding mode construction module 102, which is used to construct a sliding mode surface based on convergence speed and singular characteristics;

[0079] A control law generation module 103, which is used to construct an equivalent control law and a switching control law, wherein the equivalent control law is suitable for offsetting known disturbances, and the switching control law is suitable for offsetting unknown disturbances;

[0080] A controller module 104 for generating a closed-loop iterative controller based on the trajectory deviation;

[0081] An equation determination module 105, which is used to determine the system control equation according to the closed-loop iterative controller, the equivalent control law and the switching control law;

[0082] The robot arm control module 106 is used to control the robot arm according to the system control equation to perform a preset task.

[0083] In one embodiment, the dynamic equation of the robotic arm is:

[0084]

[0085] Where M(q) is the n×n dimensional positive definite inertia matrix, is the n×n dimensional centrifugal force and Coriolis force matrix, G(q) is the n×1 dimensional gravity term vector, the control input τ is the n×1 joint torque vector, n is the number of robot joints, q is the actual trajectory, is the time derivative of q, for The derivative with respect to time, τ d Represents an external unknown disturbance.

[0086] In one embodiment, the sliding surface is:

[0087]

[0088] Among them, α and β are normal coefficients, sign(*) is the sign function, r1 and r2 are constants, and 1 <r1<2,r1<r2。

[0089] In one implementation, the equivalent control law is:

[0090]

[0091] Among them, τ eq is the equivalent control law, m0 is the positive definite inertia matrix of the nominal model, C0 is the centrifugal force and Coriolis force matrix of the nominal model, G0 is the gravity term vector of the nominal model, q is the actual trajectory, is the time derivative of q, for The derivative with respect to time, q d is the expected trajectory, and s is the sliding mode hyperplane.

[0092] In one implementation, the switching control law is:

[0093] τ sw =M0[ks+μsat(s)]

[0094] Among them, sat(s) is the saturation function, k and μ are the reaching law parameter matrices, M0 is the positive definite inertia matrix of the nominal model, and s is the sliding mode hyperplane.

[0095] In one implementation, the closed-loop iterative controller is:

[0096]

[0097] Among them, K d , K p is the positive definite gain parameter matrix, is the error equation, u k (t) is the controller output.

[0098] In one embodiment, the system control equation is:

[0099]

[0100] u k+1 (t) = u k (t)+Γ

[0101] Among them, Γ is the intermediate parameter, u k (t) is the controller output, M0 is the positive definite inertia matrix of the nominal model, C0 is the centrifugal force and Coriolis force matrix of the nominal model, and G0 is the gravity term vector of the nominal model.

[0102] The sliding mode iterative control device for a robotic arm provided in the above-mentioned embodiment of the present application and the sliding mode iterative control method for a robotic arm provided in the embodiment of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0103] The above describes the internal functions and structure of the sliding mode iterative control device of the robot arm, such as Figure 3 As shown, in practice, the sliding mode iterative control device of the robot arm can be implemented as an electronic device, including: a memory 301 and a processor 303.

[0104] The memory 301 may be configured to store programs.

[0105] In addition, the memory 301 may also be configured to store various other data to support operations on the electronic device. Examples of such data include instructions for any application or method operating on the electronic device, contact data, phone book data, messages, pictures, videos, etc.

[0106] The memory 301 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0107] The processor 303 is coupled to the memory 301 and is configured to execute a program in the memory 301 to:

[0108] According to the parameters of the robot arm, a dynamic model of the robot arm is constructed, and model uncertainty is added to the dynamic model of the robot arm; the model uncertainty includes known disturbances and unknown disturbances;

[0109] Construct sliding surface based on convergence speed and singular characteristics;

[0110] Constructing an equivalent control law and a switching control law, wherein the equivalent control law is suitable for offsetting known disturbances, and the switching control law is suitable for offsetting unknown disturbances;

[0111] Based on the trajectory deviation, a closed-loop iterative controller is generated;

[0112] Determining a system control equation according to the closed-loop iterative controller, the equivalent control law and the switching control law;

[0113] The robot arm is controlled according to the system control equation to perform the preset task.

[0114] In one embodiment, the dynamic equation of the robotic arm is:

[0115]

[0116] Where M(q) is the n×n dimensional positive definite inertia matrix, is the n×n dimensional centrifugal force and Coriolis force matrix, G(q) is the n×1 dimensional gravity term vector, the control input τ is the n×1 joint torque vector, n is the number of robot joints, q is the actual trajectory, is the time derivative of q, for The derivative with respect to time, τ d Represents an external unknown disturbance.

[0117] In one embodiment, the sliding surface is:

[0118]

[0119] Among them, α and β are normal coefficients, sign(*) is the sign function, r1 and r2 are constants, and 1 <r1<2,r1<r2。

[0120] In one implementation, the equivalent control law is:

[0121]

[0122] Among them, τ eq is the equivalent control law, M0 is the positive definite inertia matrix of the nominal model, C0 is the centrifugal force and Coriolis force matrix of the nominal model, G0 is the gravity term vector of the nominal model, q is the actual trajectory, is the time derivative of q, for The derivative with respect to time, q d is the expected trajectory, and s is the sliding mode hyperplane.

[0123] In one implementation, the switching control law is:

[0124] τ sw =M0[ks+μsat(s)]

[0125] Among them, sat(s) is the saturation function, k and μ are the reaching law parameter matrices, M0 is the positive definite inertia matrix of the nominal model, and s is the sliding mode hyperplane.

[0126] In one implementation, the closed-loop iterative controller is:

[0127]

[0128] Among them, K d , K p is the positive definite gain parameter matrix, is the error equation, u k (t) is the controller output.

[0129] In one embodiment, the system control equation is:

[0130]

[0131] u k+1 (t) = u k (t)+Γ

[0132] Among them, Γ is the intermediate parameter, u k (t) is the controller output, M0 is the positive definite inertia matrix of the nominal model, C0 is the centrifugal force and Coriolis force matrix of the nominal model, and G0 is the gravity term vector of the nominal model.

[0133] In the present application, the processor is also specifically used to execute all processes and steps of the sliding mode iterative control method of the above-mentioned robotic arm. The specific content can be referred to the records in the sliding mode iterative control method of the robotic arm, and will not be repeated in this application.

[0134] In this application, Figure 3 Only some components are shown schematically, which does not mean that the electronic device only includes Figure 3 Components shown.

[0135] The electronic device provided in this embodiment is based on the same inventive concept as the sliding mode iterative control method of the robotic arm provided in the embodiment of the present application, and has the same beneficial effects as the method adopted, run or implemented by the application program stored therein.

[0136] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0137] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0138] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0139] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0140] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0141] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0142] The present application also provides a computer-readable storage medium corresponding to the sliding mode iterative control method of the robotic arm provided in the aforementioned embodiment, on which a computer program (i.e., a program product) is stored. When the computer program is run by a processor, it will execute the sliding mode iterative control method of the robotic arm provided in any of the aforementioned embodiments.

[0143] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0144] The computer-readable storage medium provided in the above-mentioned embodiments of the present application and the sliding mode iterative control method of the robotic arm provided in the embodiments of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0145] It should be noted that in the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known structures and technologies are not shown in detail so as not to obscure the understanding of this description.

[0146] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0147] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A sliding mode iterative control method for a robotic arm, characterized in that: include: According to the parameters of the robot arm, a dynamic model of the robot arm is constructed, and model uncertainty is added to the dynamic model of the robot arm; the model uncertainty includes known disturbances and unknown disturbances; Construct sliding surface based on convergence speed and singular characteristics; Constructing an equivalent control law and a switching control law, wherein the equivalent control law is suitable for offsetting known disturbances, and the switching control law is suitable for offsetting unknown disturbances; Based on the trajectory deviation, a closed-loop iterative controller is generated; Determining a system control equation according to the closed-loop iterative controller, the equivalent control law and the switching control law; The robot arm is controlled according to the system control equation to perform the preset task.

2. The sliding mode iterative control method of a robot arm according to claim 1, characterized in that: The dynamic equation of the robotic arm is: Where M(q) is the n×n dimensional positive definite inertia matrix, is the n×n dimensional centrifugal force and Coriolis force matrix, G(q) is the n×1 dimensional gravity term vector, the control input τ is the n×1 joint torque vector, n is the number of robot joints, q is the actual trajectory, is the time derivative of q, for The derivative with respect to time, τ d Represents an external unknown disturbance.

3. The sliding mode iterative control method of a robot arm according to claim 1, characterized in that: The sliding surface is: Among them, α and β are normal coefficients, sign(*) is the sign function, r1 and r2 are constants, and 1 <r1<2,r1<r2。 4. The sliding mode iterative control method of a robot arm according to claim 1, characterized in that: The equivalent control law is: Among them, τ eq is the equivalent control law, M0 is the positive definite inertia matrix of the nominal model, C0 is the centrifugal force and Coriolis force matrix of the nominal model, G0 is the gravity term vector of the nominal model, q is the actual trajectory, is the time derivative of q, for The derivative with respect to time, q d is the expected trajectory, and s is the sliding mode hyperplane.

5. The sliding mode iterative control method of a robot arm according to claim 1, characterized in that: The switching control law is: t sw =M0[ks+μsat(s)] Among them, sat(s) is the saturation function, k and μ are the reaching law parameter matrices, M0 is the positive definite inertia matrix of the nominal model, and s is the sliding mode hyperplane.

6. The sliding mode iterative control method of a robot arm according to claim 1, characterized in that: The closed-loop iterative controller is: Among them, K d , K p is the positive definite gain parameter matrix, is the error equation, u k (t) is the controller output.

7. The sliding mode iterative control method of a robot arm according to claim 1, characterized in that: The control equation of the system is: u k+1 (t)=u k (t)+Γ Among them, Γ is the intermediate parameter, u k (t) is the controller output, M0 is the positive definite inertia matrix of the nominal model, C0 is the centrifugal force and Coriolis force matrix of the nominal model, and G0 is the gravity term vector of the nominal model.

8. A sliding mode iterative control device for a robotic arm, characterized in that: include: A model building module, which is used to build a mechanical arm dynamics model according to the mechanical arm parameters, and add model uncertainty to the mechanical arm dynamics model; the model uncertainty includes known disturbances and unknown disturbances; A sliding mode construction module, which is used to construct the sliding mode surface based on the convergence rate and singular characteristics; A control law generation module, which is used to construct an equivalent control law and a switching control law, wherein the equivalent control law is suitable for offsetting known disturbances, and the switching control law is suitable for offsetting unknown disturbances; A controller module, which is used to generate a closed-loop iterative controller based on the trajectory deviation; An equation determination module, which is used to determine the system control equation according to the closed-loop iterative controller, the equivalent control law and the switching control law; The robot arm control module is used to control the robot arm according to the system control equation to perform a preset task.

9. An electronic device, characterized in that: include: Memory and processor; The memory is used to store programs; The processor, coupled to the memory, is configured to execute the program to: According to the parameters of the robot arm, a dynamic model of the robot arm is constructed, and model uncertainty is added to the dynamic model of the robot arm; the model uncertainty includes known disturbances and unknown disturbances; Construct sliding surface based on convergence speed and singular characteristics; Constructing an equivalent control law and a switching control law, wherein the equivalent control law is suitable for offsetting known disturbances, and the switching control law is suitable for offsetting unknown disturbances; Based on the trajectory deviation, a closed-loop iterative controller is generated; Determining a system control equation according to the closed-loop iterative controller, the equivalent control law and the switching control law; The robot arm is controlled according to the system control equation to perform the preset task.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the sliding mode iterative control method for a robotic arm as described in any one of claims 1 to 7.

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