Increased transient performance for the adaptive control of feedback linearizable systems using multiple models

Abstract

We consider a class of minimum-phase non-linear systems with large parametric uncertainties. The non-linear dynamics is assumed to be linearly parameterized in terms of the unknown parameters. A novel scheme which utilizes multiple models in a model reference adaptive control (MRAC) framework is proposed to improve the transient performance of the adaptive scheme. The proposed approach makes use of fixed models from a compact and partitioned parameter space and resets the parameter update dynamics to the model which gives a negative jump to the control Lyapunov function. The overall stability of closed loop system under the switching is preserved based on the Lyapunov approach. A simulation study is given in order to demonstrate the efficient use of the algorithm.

Acknowledgements

This work is partly sponsored by the Bogazici University Research Fund under Grant No. 04A205. The authors would like to thanks anonymous reviewers for the careful review of the article and their suggestions.

The first author would like to thank Prof. K.S. Narendra for introducing him to the multiple model based adaptive control concepts.