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Proceedings Paper

Design of a sliding mode control scheme using neural networks
Author(s): Dong-Wook Lee; Jeong-Ho Cho; Young-Tae Kim
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Paper Abstract

In this paper, a new control strategy is presented that combines sliding mode control theory with a neural network. Sliding mode control theory requires the complete knowledge of the dynamics of the controlled system. However, in practice, this could be a serious limitation on the practical usefulness of sliding mode control theory. A multilayer neural network with a back-propagation learning algorithm is employed to solve this kind of problem. The neural network serves as a compensator without a priori knowledge about the system. The robustness against parameter uncertainty and nonlinearity, and the effectiveness of the proposed algorithm is verified by simulation results.

Paper Details

Date Published: 4 April 1997
PDF: 10 pages
Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); doi: 10.1117/12.271526
Show Author Affiliations
Dong-Wook Lee, Dongguk Univ. (South Korea)
Jeong-Ho Cho, Dongguk Univ. (South Korea)
Young-Tae Kim, Dongguk Univ. (South Korea)


Published in SPIE Proceedings Vol. 3077:
Applications and Science of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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