Nonlinear systems identification and control via dynamic multitime scales neural networks

IEEE Transactions on Neural Networks and Learning Systems

Volumn 24, Issue 11, 2013, Pages 1814-1823

  Fu, Zhi Jun ^a   Xie, Wen Fang ^b   Han, Xuan ^b   Luo, Wei Dong ^c  

^a ZHEJIANG UNIVERSITY OF TECHNOLOGY   (China)

^b Dept of Electrical and Computer Engineering   (Canada)

^c UNIVERSITY OF SCIENCE AND TECHNOLOGY BEIJING   (China)

Author keywords

Dynamic multitime scale neural networks; neural network controller; nonlinear systems; online identification

Indexed keywords

BETTER PERFORMANCE; MULTITIME SCALE NEURAL NETWORKS; NEURAL NETWORK CONTROLLERS; NONLINEAR IDENTIFICATIONS; NONLINEAR SYSTEMS IDENTIFICATION; ON-LINE IDENTIFICATION; SINGULARLY PERTURBED; TRAJECTORY TRACKING;

ALGORITHMS; LYAPUNOV FUNCTIONS; MULTILAYER NEURAL NETWORKS; NONLINEAR SYSTEMS; PERTURBATION TECHNIQUES; SYSTEM STABILITY;

IDENTIFICATION (CONTROL SYSTEMS);

ALGORITHM; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; FEEDBACK SYSTEM; NONLINEAR SYSTEM; PROCEDURES; THEORETICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; FEEDBACK; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; PATTERN RECOGNITION, AUTOMATED;

EID: 84886950724     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2013.2265604     Document Type: Article

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