DISTURBANCES REJECTION CONTROL FOR DUAL ARMS ROBOT USING ARTIFICIAL NEURAL NETWORK

Abstract

This paper presents a disturbances rejection control method for dual arms
robots using artificial neural networks. By updating the network parameters to
minimize input disturbances, the system's state trajectory is guaranteed to
follow the reference signal regardless of whether disturbances are present. The
Matlab/Simulink software simulation results show the proposed method's
effectiveness and advantages over sliding mode controllers.