Robotic trajectory tracking control system based on fuzzy neural network

Abstract

The manipulator system is a multi-input and multi-output system with highly coupled, nonlinear and other dynamic characteristics, and the system structure and parameters are unpredictable in practice. A fuzzy neural network controller is designed for this system, and the parameters of FNNC are optimized by combining particle swarm algorithm and BP algorithm. The experimental results show that the scheme has strong adaptability, stability and anti-interference performance for the control system, and effectively solves the trajectory tracking problem of the manipulator.