New Time-Efficient Structure for Observer-Based Adaptive Fuzzy-Neural Controllers for Nonaffine Nonlinear Systems
學年 98
學期 2
出版（發表）日期 2010-03-01
作品名稱 New Time-Efficient Structure for Observer-Based Adaptive Fuzzy-Neural Controllers for Nonaffine Nonlinear Systems
作品名稱（其他語言）
著者 Wei Yen Wang; I. Hsum Li; Ming Chang Chen; Shun Feng Su; Yih Guang Leu
單位
出版者
著錄名稱、卷期、頁數 International Journal of Innovative Computing, Information and Control 6(3), p.963-978
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.
關鍵字 Software;Theoretical Computer Science;Information Systems;Computational Theory and Mathematics
語言 en
ISSN
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 是
國別 JPN
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/115949 )

SDGS 產業創新與基礎設施