Predictive Trajectory Tracking Control for Mobile Robots

Abstract

A model predictive trajectory tracking control applied to a mobile robot is presented in this paper. Prediction model derived from linearized tracking error dynamics is used to predict future system behavior. A control law is derived from quadratic cost function consisting of system tracking error and control effort. Experimental results on a real mobile are presented and a comparison of the obtained control to a time-varying state feedback controller is given. The proposed controller includes velocity and acceleration constraints to prevent mobile robot from slipping and a Smith predictor is used to compensate for vision system dead-time. Some future work ideas are discussed as well.