Cooperative Control of Backstepping Neural Network and Port-Controlled Hamiltonian for Robot System

Abstract

It is difficult for a single control method to track the position quickly and accurately at the end of the robot. To solve this problem, a cooperative control strategy of backstepping adaptive neural network (BS-RBFNN) signal control and port controlled Hamiltonian (PCH) energy control is proposed. BS-RBFNN solves the problem of rapidity when the system is in dynamic state, PCH control solves the problem of accuracy when the system is in steady state. The cooperative function based on the error is designed, and the cooperative control of the robot joint system is realized by using this function. The robot joint position servo system can not only realize the rapid adjustment of the dynamic position, but also realize the high precision tracking control in the steady state. Simulation results show that the system achieves fast dynamic response and accurate steady-state position tracking by using cooperative control method.