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Mechanical arm input saturation fixed time trajectory tracking control method and system

A fixed time, trajectory tracking technology, applied in the direction of manipulators, program control manipulators, manufacturing tools, etc., can solve the problems of inaccuracy and speed

Active Publication Date: 2020-08-07
UNIV OF SCI & TECH BEIJING
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, these existing trajectory tracking control methods cannot overcome the inaccurate and fast problem of the trajectory tracking control of the manipulator caused by the uncertainty of the dynamic model, coupling effects and external unknown disturbance factors; therefore, it is urgent to explore an effective The trajectory tracking control technology of the manipulator

Method used

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  • Mechanical arm input saturation fixed time trajectory tracking control method and system
  • Mechanical arm input saturation fixed time trajectory tracking control method and system
  • Mechanical arm input saturation fixed time trajectory tracking control method and system

Examples

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no. 1 example

[0101] First of all, it needs to be explained that the artificial neural network has the ability to map the input-output relationship only by using the prior input-output information. Because the neural network has good function approximation ability, it is widely used in the control of uncertain nonlinear systems. design.

[0102] The method based on Radial Basis Function Neural Network (RBFNN) is feasible to approximate nonlinear functions with arbitrary precision under certain conditions. With no or relatively limited knowledge of system dynamics, it is possible to efficiently construct a controller to achieve mission control. There are a large number of examples of intelligent control methods such as sliding mode control, dynamic surface control, impedance control, and fuzzy logic control in engineering.

[0103] Reinforcement learning is different from supervised learning in that it is a learning method that obtains training information from the environment and is an eva...

no. 2 example

[0251] This embodiment provides a trajectory tracking control system for fixed time input saturation of a manipulator, which includes:

[0252] The expected trajectory and state data acquisition module of the mechanical arm is used to obtain the expected trajectory of the mechanical arm, and obtain the state data of the mechanical arm through the sensor of the mechanical arm;

[0253] The reinforcement learning control module is used to suppress the model uncertainty of the mechanical arm by using the reinforcement learning control algorithm according to the acquired state data;

[0254] The nonlinear anti-saturation compensator design module is used to design the nonlinear anti-saturation compensator to compensate the saturation overflow effect of the joint torque actuator in real time;

[0255] Non-singular fast terminal sliding mode controller is used to design a non-singular fast terminal sliding mode controller, so that the tracking error of the joint trajectory of the ma...

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Abstract

The invention provides a mechanical arm input saturation fixed time trajectory tracking control method and system. The method includes the steps that a desired trajectory of a mechanical arm is obtained, and state data of the mechanical arm are obtained through a mechanical arm sensor; a reinforcement learning control algorithm is adopted to suppresses the model uncertainty of the mechanical arm according to the obtained state data; a nonlinear anti-saturation compensator is designed to compensate for the saturation overflow effect of a joint torque actuator in real time; and a non-singular fast terminal sliding mode controller is designed to enable the joint trajectory tracking error of the mechanical arm to converge to the small neighborhood of an origin within a fixed time, and the input saturation fixed time desired trajectory tracking control of the mechanical arm is realized. The mechanical arm input saturation fixed time trajectory tracking control method and system have the online learning ability of model uncertainty, so that the mechanical arm can accurately and quickly track a trajectory.

Description

technical field [0001] The invention relates to the technical field of trajectory tracking of a robotic arm, in particular to a method and system for controlling trajectory tracking of a robotic arm with input saturation at fixed time based on reinforcement learning. Background technique [0002] Manipulators are widely used in dangerous environments such as military, manufacturing, and medical environments. The trajectory tracking control technology of manipulators has always been one of the hot research directions. The movement of manipulators according to the joint trajectories set in advance is the key to realizing these complex tasks. The key to the mission; however, it is very difficult for the manipulator to track the trajectory accurately and quickly due to the uncertainty of the dynamic model, coupling effects and external unknown interference problems. [0003] In recent years, many trajectory tracking control methods have appeared, including PID control, adaptive ...

Claims

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Application Information

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IPC IPC(8): B25J9/16
CPCB25J9/1605B25J9/163B25J9/1664
Inventor 孙亮曹胜杰
Owner UNIV OF SCI & TECH BEIJING
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