Sliding Mode Observer-Based Synthesis of State Derivative-Free Model Reference Adaptive Control of Distributed Parameter Systems

Author:

Orlov Y. V.1

Affiliation:

1. Electronics and Telecommunication Department, CICESE Research Center, Mexico, P.O. Box 434944 San Diego, CA 92143-4944

Abstract

This paper presents control laws for distributed parameter systems of parabolic and hyperbolic types which, on the one hand ensure robustness with respect to small dynamic uncertainties and disturbances, and on the other hand, permit on-line plant parameter estimation. The novelty of the algorithms proposed is (a) in the construction of a sliding mode-based state derivative observer and (b) in the inclusion of this observer into a model reference adaptive controller which thereby regularizes the ill-posed identification problem itself. Apart from this, the controllers constructed do not suffer from on-line computation of spatial derivatives of the measurement data, and hence they are of reduced sensitivity with respect to the measurement noise. [S0022-0434(00)02104-3]

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Reference11 articles.

1. Landau, Y. D., 1979, Adaptive Control - The Model Reference Approach. Marcel Dekker, New York.

2. Bentsman, J., and Orlov, Y. V., “Reduced spatial order model reference adaptive control of spatially varying distributed parameter systems of parabolic and hyperbolic types,” Int. J. Adapt. Control Signal Proc. (to be published).

3. Bo¨hm, M., Demetriou, M. A., Reich, S., and Rosen, I. G., 1997, “Model reference adaptive control of distributed parameter systems,” SIAM J. Control Optim., 35, pp. 678–713.

4. Hong, K. S., and Bentsman, J., 1994, “Direct adaptive control of parabolic systems: algorithm synthesis and convergence and stability analysis,” IEEE Trans. Autom. Control, AC-39, pp. 2018–2033.

5. Bamieh, B. A., 1997, “The structure of optimal controllers of spatially-invariant distributed parameter systems,” Proc. 36th IEEE Conf. on Decision and Control, pp. 1056–1061.

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