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Fuzzy-neural network adaptive sliding mode tracking control for interconnected system
Zhang, Yan-xin; Dong, Hai-rong; Huang, DS; Li, K; Irwin, GW
刊名COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS
2006
卷号4114页码:127-133
英文摘要Fuzzy neural network adaptive tracking controller is designed to realize the tracking control for a class of unknown nonlinear interconnected systems. No constraint or matching conditions of the uncertain terms are required. For the low dimensions unknown dynamic of the subsystems and the high one of the interconnected terms, two classes of fuzzy rules are adopted respectively to approximate the unknowns. The neural network is used to counteract the extra gains of the controller. The fuzzy sliding mode control is developed to compensate for the exterior disturb and the fuzzy neural network approximation errors. By the Simultaneity, based on Lyapunov method, the parameters of the systems are regulated on line by the adaptive laws. Global asymptotic stability is assured with the tracking errors converging to a neighborhood of zero.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence
研究领域[WOS]Computer Science
收录类别ISTP ; SCI
语种英语
WOS记录号WOS:000240083300016
公开日期2015-12-24
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/9208]  
专题自动化研究所_09年以前成果
作者单位1.Beijing Jiaotong Univ, Sch Elect & Informat Engn, Inst Automat Control, Beijing 100044, Peoples R China
2.Chinese Acad Sci, Key Lab Complex Syst & Intelligence Sci, Beijing 100044, Peoples R China
推荐引用方式
GB/T 7714
Zhang, Yan-xin,Dong, Hai-rong,Huang, DS,et al. Fuzzy-neural network adaptive sliding mode tracking control for interconnected system[J]. COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS,2006,4114:127-133.
APA Zhang, Yan-xin,Dong, Hai-rong,Huang, DS,Li, K,&Irwin, GW.(2006).Fuzzy-neural network adaptive sliding mode tracking control for interconnected system.COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS,4114,127-133.
MLA Zhang, Yan-xin,et al."Fuzzy-neural network adaptive sliding mode tracking control for interconnected system".COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS 4114(2006):127-133.
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