Trajectory Tracking Control of Manipulator Based on Particle Swarm Optimization Fuzzy Neural Network

Abstract

The manipulator system is a multi-input and multi-output system with highly coupling and nonlinear dynamics characteristics, and the system structure and parameters have many unpredictable factors in practical work. A fuzzy neural network model controller is proposed, and the parameters of the controller are optimized by particle swarm optimization algorithm. The simulation results show that the control strategy has strong adaptability, stability and anti-interference performance to the control system, and effectively solves the trajectory tracking problem of the manipulator.