CMAC-based integral variable structure control of nonlinear system
Resource
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Journal
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Pages
-
Date Issued
2002-05
Date
2002-05
Author(s)
Lin, Wei-Song
Hung, Chin-Pao
DOI
N/A
Abstract
A CMAC-based controller with a compensating neural network and an update rule is proposed to design the integral variable structure control (IVSC) of a nonlinear system. The control scheme comprises a soft supervisor controller and a CMAC neural network. Based on the Lyapunov theorem, the soft supervisor controller guarantees the global stability of the system. The CMAC neural network provides a compensatory signal to perform the equivalent control by a real-time learning algorithm. The new IVSC control scheme reduced the dependency on system parameters and eliminated the chattering of the control signal through learning. It is proved that the CMAC-based IVSC (CIVSC) scheme is globally stable in the sense that all signals involved are bounded and the tracking error will converge to zero. Simulation results of numerical example demonstrate the effectiveness and robustness of the proposed controller.
Type
journal article
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