New Time-Efficient Structure for Observer-Based Adaptive Fuzzy-Neural Controllers for Nonaffine Nonlinear Systems

淡江大學機構典藏 > 工學院 > 機械與機電工程學系暨研究所 > 期刊論文 > Item 987654321/115949

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題名:	New Time-Efficient Structure for Observer-Based Adaptive Fuzzy-Neural Controllers for Nonaffine Nonlinear Systems
作者:	Wang, Wei Yen;Li, I. Hsum;Chen, Ming Chang;Su, Shun Feng;Leu, Yih Guang
關鍵詞:	Software;Theoretical Computer Science;Information Systems;Computational Theory and Mathematics
日期:	2010-03
上傳時間:	2019-03-13 12:10:16 (UTC+8)
摘要:	This paper proposes an observer-based adaptive controller with a merged fuzzy-neural network for nonaffine nonlinear systems under the constraint that only the system output is available for measurement. Using a conventional fuzzy-neural network leads to rule explosion which leads to huge computation time. Our proposed merged-FNN does not have this problem, and can take the place of the conventional fuzzy-neural networks under some assumptions while maintaining the property of stability. Moreover, the adaptive scheme using the merged-FNN guarantees that all signals involved are bounded and the output of the closed-loop system asymptotically tracks the desired output trajectory. Finally, this paper gives examples of the proposed controller for nonaffine nonlinear systems, and is shown to provide good effectiveness.
關聯:	International Journal of Innovative Computing, Information and Control 6(3), p.963-978
顯示於類別:	[機械與機電工程學系暨研究所] 期刊論文

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