Fuzzy control for nonlinear systems via neural-network-based approach

Feng Hsiag Hsiao, Wei Ling Chiang, Cheng Wu Chen

研究成果: 雜誌貢獻期刊論文同行評審

35 引文 斯高帕斯(Scopus)

摘要

The stabilization problem is considered in this study for a nonlinear system. It is shown that the stability analysis of nonlinear systems can be reduced into linear matrix inequality (LMI) problems. First, the neural-network (NN) model is employed to approximate a nonlinear system via the back propagation algorithm. Then, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. In terms of Lyapunov’s direct method, a sufficient condition is provided to guarantee the stability of nonlinear systems. Based on this criterion, a model based fuzzy controller is then designed to stabilize the nonlinear system and the H control performance is achieved at the same time. Finally, two examples with numerical simulations are given to illustrate the control methodology.

原文???core.languages.en_GB???
頁(從 - 到)145-152
頁數8
期刊International Journal of Computational Methods in Engineering Science and Mechanics
6
發行號3
DOIs
出版狀態已出版 - 2005

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