Finite time neural network optimization method for solving inverse kinematics of redundant manipulator

Abstract

The invention discloses a finite time neural network optimization method for solving the inverse kinematics of a redundant manipulator. The finite time neural network optimization method comprises thefollowing steps that 1), an expected target track r*(t) and a joint angel theta*(0) expected to be returned of an end effector of the redundant manipulator are determined, and the end effector of the manipulator is deviated from the position of the expected track; 2), final state attraction optimization indexed are designed, a quadratic programming scheme based on the final state attraction is constructed, wherein an initial joint angle of the redundant manipulator during actual movement can be arbitrarily designated, the initial joint angle theta(0) of the redundant manipulator during actual movement is given, theta(0) is taken as a motion starting point, and the formed repeated motion programming scheme is described as the quadratic programming with the final state attractor optimization indexes; 3) a final state neural network model of a finite value activation function is constructed, and a finite value final state neural network is used for solving a time-varying matrix equation; and 4), the result which is obtained by solving the equation is used for controlling each joint motor to drive the manipulator to execute tasks. The finite time neural network optimization method has the advantages of being high in precision and capable of converging in finite time.

Description

technical field [0001] The present invention relates to repetitive motion planning and control technology of a redundant mechanical arm, in particular to a finite time convergence performance index and an inverse kinematics solution method of a redundant mechanical arm in the case of an initial offset. Background technique [0002] The progress of society and the development of science and technology have prompted people to be more and more eager to be liberated from monotonous, repetitive, complicated and dangerous labor work, and the mechanical arm (as one of the major achievements of human scientific and technological progress in the 20th century) The emergence of this makes all this gradually become a reality. Generally speaking, a robotic arm refers to a mechanical device with an active end, and its end tasks include handling, welding, painting, and assembly; it has been widely used in industrial manufacturing, medical treatment, entertainment services, fire protection,...

AI Technical Summary

Problems solved by technology

[0012] In order to overcome the shortcomings of the existing inverse kinematics solution method for redundant manipulators, which have low precision and cannot achieve convergence in a limited time, the present invention provides a method based on final state attraction optimization index with high precision, convergence in a limited time, and easy implementation. The trajectory planning method of the redundant manipulator uses the final state neural network with a finite value activation function as the solver. In the case of the initial position deviation, the joint angles of the redundant manipulator can still return to the initial desired position

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