Research on Robot Motion Control Based on Variable Structure Fuzzy Neural Network Based on T-S Model

Abstract

The motion robot system is a nonlinear, strong coupling, non-integrity constraint control system, and its motion control has always been a hot topic in the control field. Aiming at the problem that the fuzzy neural network controller has too large computational complexity and poor anti-interference ability to the outside world, the paper proposes a fuzzy neural network control algorithm for TS, which reduces the computational complexity of the neural network and makes the closed-loop system of the robot more stable. The simulation experiment proves that the fuzzy neural network algorithm based on T-S makes the controller more resistant to external disturbances, and can maintain a high level of control even in harsh environments.