Nonlinear adaptive control method and system for use in motion control of robotic arms

Abstract

The present invention discloses a nonlinear adaptive control method and system for use in the motion control of a robot arm, the method including steps such as inputting the output of an incremental nonlinear dynamic inversion controller to a servo motor driver for driving a robot arm, and the system is used to realize the method. The present invention does not require a robot arm motion load model and a disturbance model for tuning the parameters of the controller, thus solving the technical problems of the conventional robot arm motion control technology, that is, the motion load model is difficult to identify and the controller's time-varying parameters must be tuned. In the current situation where the conventional technology cannot effectively solve the above difficulties and problems, the present invention provides a very simple, effective and high-performance robot arm motion control method and system.

Description

[Technical field]

[0001] The present invention relates to the field of robotic arm motion control, and more particularly to a nonlinear adaptive control method and system used in robotic arm motion control. [Background technology]

[0002] With the development of intelligent technology, smart devices and intelligent technologies are increasingly used in people's lives, work and learning, which improves people's quality of life and improves people's learning and work efficiency.In the field of robot arm motion control, the robot arm system is inherently a nonlinear, time-varying and uncertain system, and the control system design requires the use of nonlinear and adaptive control algorithms.

[0003] At present, all algorithms of robot arm motion control systems use traditional PID control algorithms. PID control algorithms are control algorithms based on linear systems, and the problem when using PID algorithms to control the motion of nonlinear robot arms is how to tune the PID ratio, integral and differential parameters. Because the robot arm system is nonlinear, time-varying and uncertain, it is necessary to identify the nonlinear model or linearized model of the robot arm and its load and disturbance offline or online. The obtained robot arm, load and disturbance models are used to tune the PID parameters in real time or stepwise. In the entire control process, the parameters of the traditional PID algorithm are constants. In practice, the entire controlled system cannot be predicted early, especially the motion and location environment of the general-purpose robot arm cannot be predicted, so the fixed PID parameters cannot achieve high-performance control effect for the system. Although model identification can achieve relatively intuitive control performance, model identification, especially for online model identification, greatly increases the complexity of the system, and it is not possible to ensure that accurate models and model parameters are obtained, and such adaptive control systems are difficult to obtain industrial certification. In addition, other adaptive or intelligent control methods, including fuzzy control, sliding mode control, neural network control, model reference adaptation, etc., have problems in that they cannot guarantee algorithm stability and stable operation in any operating condition and load interference environment. No effective solution to the above problem has yet been proposed. Summary of the Invention

[0004] Therefore, an object of the present invention is to provide a nonlinear adaptive control method and system for motion control of a robot arm. The present invention does not require a robot arm motion load model and a disturbance model for tuning the parameters of the controller, and therefore solves the technical problems of the conventional robot arm motion control technology, that is, the motion load model is difficult to identify and the controller's time-varying parameters must be tuned. In the current situation where the conventional technology cannot effectively solve the above-mentioned difficulties and problems, the present invention provides a very simple, effective and high-performance robot arm motion control method.

[0005] In order to achieve the above object, the motion control method of the robot arm used in the motion control of the robot arm of the present invention uses the Lagrangian dynamics modeling method to establish a complete nonlinear dynamics model having n links of the robot arm correspondingly, obtains the measurement data of the joint angle q of the robot arm, and uses the numerical differentiation method to calculate the second-order time differential coefficient d of the joint angle q of the robot arm. 2 q / dt 2 and calculating the ideal value q of the joint angle of the robot arm based on the robot arm motion requirements. d and the ideal value q of the joint angle of the robot arm d The difference between the measured value q and the measured value q is input to the motion controller, and the output of the motion controller and the second order time derivative d 2 q / dt 2 and inputting a control command output from the incremental nonlinear dynamic inversion controller to a servo motor driver that drives the robot arm.

[0006] The incremental nonlinear dynamic inversion controller comprises: JPEG2025515841000002.jpg1067

[0007] JPEG2025515841000003.jpg31137

[0008] The virtual control variable of the incremental nonlinear dynamic inversion controller is JPEG2025515841000004.jpg29138

[0009] The present invention further discloses a nonlinear adaptive control system for use in motion control of a robot arm, comprising a processor and a memory, wherein the memory has computer readable instructions stored therein, and the processor is adapted to execute the computer readable instructions, wherein the computer readable instructions, when actuated, perform the above-mentioned nonlinear adaptive control method for use in motion control of a robot arm.

[0010] In the embodiment of the present invention, the second order time derivative of the robot arm joint angle (angular acceleration of the robot arm joint) is used to replace the required robot arm system, load and disturbance model, and furthermore, there is no need for a system, load and disturbance model in dynamic inversion control, thereby resolving the technical problem in conventional robot arm motion control technology that the robot arm system, load and disturbance model is difficult to identify and the time-varying parameters of the controller must be tuned.

[0011] According to another aspect of an embodiment of the present invention there is further provided a non-linear adaptive control system for motion control of a robotic arm, comprising a processor and a memory, the memory having computer readable instructions stored therein, the processor being adapted to execute the computer readable instructions, wherein the computer readable instructions, when actuated, perform a non-linear adaptive control method for use in motion control of a robotic arm. [Brief description of the drawings]

[0012] The drawings described herein are provided for a further understanding of the invention and constitute a part of this application, and the schematic embodiments of the invention and the description thereof are intended to illustrate the invention and are not intended to limit the invention. [Figure 1] 1 is a flowchart of a nonlinear adaptive control method used for motion control of a robot arm in accordance with an embodiment of the present invention. [Diagram 2] FIG. 1 is a configuration block diagram of a nonlinear adaptive control system used for motion control of a robot arm according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] In order to make those skilled in the art to better understand the solution of the present invention, the following will clearly and comprehensively describe the technical solution in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention, and it is to be understood that the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative labor should be included in the scope of the claims of the present invention.

[0014] It should be explained that the terms "first", "second", etc. in the present specification and claims and the above drawings are used to distinguish between similar objects and are not intended to describe a particular order or sequence. It should be understood that the data so used can be exchanged, where appropriate, such that the embodiments of the present invention described herein are performed in an order other than that shown or described herein. Furthermore, the terms "comprises" and "has" and any variations thereof are intended to cover non-exclusive inclusions, e.g., a process, method, system, product, or apparatus comprising a series of steps or units is not limited to those steps or units expressly recited, but may include other steps or units not expressly recited or inherent to the process, method, product, or apparatus.

[0015] According to an embodiment of the present invention, there is provided a non-linear adaptive control method for use in controlling the motion of a robotic arm, and it should be noted that the steps illustrated in the flowcharts of the drawings may be performed, for example, in a computer system as a set of computer executable commands, and that although a logical order is shown in the flowcharts, in some cases the steps may be performed in an order different from those shown or described.

[0016] FIG. 1 is a flow chart of a nonlinear adaptive control method for use in motion control of a robot arm according to an embodiment of the present invention. As shown in FIG. 1, the method includes: A step S100 of acquiring measurement data of a joint angle q of a robot arm; Using numerical differentiation, we calculate the second-order time derivative d of the joint angle q of the robot arm. 2 q / dt 2 A step S200 of calculating Ideal value q of the joint angle of a robot arm d and a step S300 of inputting the difference between the measured value q and the measured value q to a motion controller; Motion controller output and second order time derivative d 2 q / dt 2 simultaneously inputting the incremental nonlinear dynamic inversion controller; Step S500: inputting the output of the incremental nonlinear dynamic inversion controller to a servo motor driver that drives a robot arm; A step S600 of calculating an incremental output of the incremental dynamic reversal control; and calculating a motion controller S700.

[0017] Such a robot arm motion control method uses a Lagrangian dynamics modeling method to establish a complete nonlinear dynamics model having a corresponding n-link robot arm, obtains measurement data of the joint angle q of the robot arm, and uses a numerical differentiation method to calculate the second-order time differential coefficient d of the joint angle q of the robot arm. 2 q / dt 2 and calculating the ideal value q of the joint angle of the robot arm based on the robot arm motion requirements. d and robot q d Ideal value of arm joint angle q d The difference between the measured value q and the measured value q is input to the motion controller, and the output of the motion controller and the second order time derivative d 2 q / dt 2and inputting a control command output from the incremental nonlinear dynamic inversion controller to a servo motor driver that drives the robot arm.

[0018] The incremental nonlinear dynamic inversion controller comprises: JPEG2025515841000005.jpg40141

[0019] The virtual control variable of the incremental nonlinear dynamic inversion controller is JPEG2025515841000006.jpg865e=qq in the formula d is the difference between the joint angle of the robot arm and the required joint angle of the robot arm, and K p is the ratio parameter of the motion controller, and K I is the integral parameter of the motion controller, and K D is the motion controller derivative parameter.

[0020] This incremental dynamic reversal control method is obtained based on the following principle. The robot arm model established using the Lagrangian dynamics modeling method is JPEG2025515841000007.jpg43142

[0021] Equation (1) is It can also be written as JPEG2025515841000008.jpg10127.

[0022] Simplifying equation (2), JPEG2025515841000009.jpg10109.

[0023] Where: JPEG2025515841000010.jpg20126

[0024] At the sampling time, we perform a vector series expansion for equation (4), JPEG2025515841000011.jpg44142

[0025] Where: JPEG2025515841000012.jpg43123

[0026] JPEG2025515841000013.jpg14124It is also the angular acceleration of the robot arm joint at sampling time k. As can be seen from equation (2), this angular acceleration contains all the information of the system, and the angular acceleration is used in the controller to replace the system model required by the controller.

[0027] The numbers of the above embodiments of the present invention are merely for the purpose of explanation and do not indicate superiority or inferiority of the embodiments.

[0028] In the above embodiments of the present invention, the description of each embodiment has its own emphasis, and the parts not described in detail in one embodiment can be referred to the relevant description of another embodiment.

[0029] It should be understood that in some embodiments provided by the present application, the disclosed technical contents can be realized in other forms. Here, the above-described device embodiments are merely illustrative, and for example, the division of the units may be a logical function division, and may have other division modes in actual implementation, for example, multiple units or assemblies may be combined or integrated into other systems, or some features may be ignored or not implemented. Meanwhile, the mutual couplings, direct couplings, or communication connections disclosed or discussed may be indirect couplings or communication connections via some interfaces, units, or modules, and may be electrical or other forms.

[0030] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physically separate, and may be located in one place or distributed among multiple units, among which some or all of the units may be selected according to actual needs to achieve the objective of the solution of the present embodiment.

[0031] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically alone, or two or more units may be integrated into one unit. The integrated units may be realized in the form of hardware or software functional units.

[0032] The integrated unit may be realized in the form of a software functional unit and stored in one computer-readable storage medium when sold or used as an independent product. Based on such understanding, in the technical solution of the present invention, the part that essentially contributes to the prior art or all or a part of the technical solution may be embodied in the form of a software product, and the computer software product is stored in one storage medium and includes some instructions used to make one computer device (which may be a personal computer, a server, or a network device, etc.) execute all or a part of the steps of the method according to each embodiment of the present invention. The storage medium includes various media capable of storing program codes, such as a USB flash memory, a read-only memory (ROM), a random access memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.

[0033] The above content is merely a preferred embodiment of the present invention, and it should be pointed out that those skilled in the art may make some further improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be included in the scope of the claims of the present invention.

Claims

1. 1. A nonlinear adaptive control method for use in motion control of a robot arm, comprising: Utilizing Lagrangian dynamics modeling method to establish a complete nonlinear dynamics model having a corresponding n-link robot arm; Acquiring measurement data of a joint angle q of a robot arm; Using numerical differentiation, the second time derivative of the joint angle q of the robot arm (d ２ q) / dt ２ Calculating Based on the robot arm motion requirements, the ideal value q of the robot arm joint angle is ｄ And Ideal value q of the joint angle of the robot arm ｄ and inputting the difference between the measured value q and the measured value q to a motion controller; The output of the motion controller and the second derivative (d ２ q) / dt ２ simultaneously inputting the incremental nonlinear dynamic inversion controller; and inputting an output value of the incremental nonlinear dynamic inversion controller to a servo motor driver that drives the robot arm.

2. The incremental nonlinear dynamic inversion controller comprises: In the formula, Δu is the output command of the incremental nonlinear dynamic inversion controller, q is the joint angle of the robot arm, and M(q) is the inertia matrix of the robot arm model.

2. The nonlinear adaptive control method used for motion control of a robot arm according to claim 1, wherein v is a virtual control variable of the incremental nonlinear dynamic inversion controller, and v is a joint angular acceleration of the robot arm calculated from the joint angle q of the robot arm.

3. The virtual control variable of the incremental nonlinear dynamic inversion controller is In the formula, e = q - q ｄ is the difference between the joint angle of the robot arm and the required joint angle of the robot arm, and K ｐ is the ratio parameter of the motion controller, and K Ｉ is the integral parameter of the motion controller, and K Ｄ 3. The nonlinear adaptive control method for use in motion control of a robot arm according to claim 2, wherein: is a motion controller differential parameter.

4. 1. A nonlinear adaptive control system for use in motion control of a robot arm, comprising: A nonlinear adaptive control system for use in controlling the movement of a robot arm, comprising a processor and a memory, the memory having computer readable instructions stored therein, the processor being adapted to execute the computer readable instructions, wherein the computer readable instructions, when actuated, perform a nonlinear adaptive control method for use in controlling the movement of a robot arm as described in any one of claims 1 to 3.

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