Control the Scara robot based on neural network and sliding mode control

Abstract

The paper presents an adaptive sliding mode control synthesis method for a Scara robot with uncertain parameters based on robot model identification and sliding control. The robot's dynamic equation is identified using adaptive control and neural network techniques, and the identification results are used to synthesize a trajectory-tracking sliding mode control system for the Scara robot. The control law obtained from the article has a good trajectory tracking quality.