Please use this identifier to cite or link to this item: http://rportal.lib.ntnu.edu.tw:80/handle/77345300/31930
Title: A New Time-Efficient Structure for Observer-Based Adaptive Fuzzy-Neural Controllers for Nonaffine Nonlinear Systems
Authors: 國立臺灣師範大學電機工程學系
W.-Y. Wang
I-H. Li
M.-C. Chen
S.-F. Su
Y.-G. Leu
Issue Date: 1-Mar-2010
Publisher: ICIC International
Abstract: 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.
URI: http://rportal.lib.ntnu.edu.tw/handle/77345300/31930
ISSN: 1349-4198
Other Identifiers: ntnulib_tp_E0604_01_008
Appears in Collections:教師著作

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