GA-based adaptive fuzzy-neural control for a class of MIMO systems

Yih Guang Leu*, Chin Ming Hong, Hong Jian Zhon

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

1 引文 斯高帕斯(Scopus)

摘要

A GA-based adaptive fuzzy-neural controller for a class of multi-input multi-output nonlinear systems, such as robotic systems, is developed for using observers to estimate time derivatives of the system outputs. The weighting parameters of the fuzzy-neural controller are tuned on-line via a genetic algorithm (GA). For the purpose of on-line tuning the weighting parameters of the fuzzy-neural controller, a Lyapunov-based fitness function of the GA is obtained. Besides, stability of the closed-loop system is proven by using strictly-positive-real (SPR) Lyapunov theory. The proposed overall scheme guarantees that all signals involved are bounded and the outputs of the closed-loop system track the desired output trajectories. Finally, simulation results are provided to demonstrate robustness and applicability of the proposed method.

原文英語
主出版物標題Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
發行者Springer Verlag
頁面45-53
頁數9
版本PART 1
ISBN(列印)9783540723820
DOIs
出版狀態已發佈 - 2007 一月 1
事件4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, 中国
持續時間: 2007 六月 32007 六月 7

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
號碼PART 1
4491 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

其他

其他4th International Symposium on Neural Networks, ISNN 2007
國家/地區中国
城市Nanjing
期間2007/06/032007/06/07

ASJC Scopus subject areas

  • 理論電腦科學
  • 電腦科學(全部)

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