Far East Journal of Experimental and Theoretical Artificial Intelligence
Volume 3, Issue 1, Pages 53 - 67
(February 2009)
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CMAC-BASED BOUND LIMITED COMPENSATOR IN SUPERVISORY CONTROL FOR UNCERTAIN NONLINEAR CONTROL SYSTEMS
Ted Tao (Taiwan) and Wen-Chih Yang (Taiwan)
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Abstract:
In this paper, a novel cerebellar model articulation controller (CMAC)-based bound limited compensator is proposed in supervisory control for uncertain nonlinear systems. There are two structures in the proposed schemes: one is supervisory controller and the other is the CMAC-based compensator. The supervisory controller can ensure Lyapunov stability of the controlled system in the presence of significant plant uncertainties, if the perfect control is estimated. The CMAC is employed to learn the perfect control, but a model error will exist in the learning process. The object of CMAC-based compensator is to suppress this model error, so that the supervisory control can be rationalized for uncertain nonlinear systems. Finally, simulation results demonstrate that the CMAC-based compensator not only can limit the bound required in supervisory controllers, but also can significantly improve the control performance. |
| Keywords and phrases: CMAC, supervisory control, Lyapunov stability. |
| Communicated by Shun-Feng Su |
| Number of Downloads: 247 | Number of Views: 354 |
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