Robust Tracking Control for Robots With Bounded Input

Abstract

A novel approach to robust tracking control synthesis is presented. Information about the input (control) constraints is fully exploited to achieve a simple algorithm, independent of the extent of model uncertainty. The control law is accelerometer-free (or even tacho-free, also), robust to sensor noise and allows the prespecification of the error decay rate. It is realistic from the engineering standpoint and can be implemented using current microprocessor technology. Practical tracking is proved by means of Lyapunov methodology. A simulation illustrates the effectiveness of the proposed approach.