Robust adaptive control of nonholonomic mobile robot with parameter and nonparameter uncertainties

This paper considers the tracking-control problem of a nonholonomic wheeled mobile robot with both parameter and nonparameter uncertainties. A robust adaptive controller is proposed with the aid of the adaptive backstepping technique and the learning ability of neural networks. The proposed controller guarantees that the tracking error converges to a small hall containing the origin. The hall's radius can be adjusted by control parameters. The proposed controller is successfully implemented in our simulator.

I. Introduction

In recent years, there has been a growing interest in the design of feedback-control laws for mechanical systems subjected to nonholonomic constraints. Due to Brockett's necessary condition for asymptotic feedback stabilization [1], a nonholonomic system cannot be asymptotically stabilized to a equilibrium by any smooth or continuous pure-state feedback law. To overcome this limitation, several approaches have been proposed in last decade (see [18], [20], and the references therein). Fig. 1. Configuration of a wheeled mobile robot.