RCMAC-based adaptive control for uncertain nonlinear systems

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 37, Issue 3, 2007, Pages 651-666

  Peng, Ya Fu ^a   Lin, Chih Min ^b  

^a CHING YUN UNIVERSITY   (Taiwan)

^b YUAN ZE UNIVERSITY   (Taiwan)

Author keywords

Adaptive control; Nonlinear systems; Recurrent cerebellar model articulation controller (RCMAC); Sliding mode control (SMC)

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; APPROXIMATION THEORY; BRAIN MODELS; COMPUTER SIMULATION; DYNAMIC RESPONSE; FEEDBACK CONTROL; LEARNING SYSTEMS; LYAPUNOV METHODS; SLIDING MODE CONTROL; UNCERTAIN SYSTEMS;

APPROXIMATION ERROR; CONVENTIONAL STATIC CEREBELLAR MODEL; RECURRENT CEREBELLAR MODEL ARTICULATION CONTROLLER (RCMAC);

NONLINEAR CONTROL SYSTEMS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOMIMETICS; CEREBELLUM; COMPUTER SIMULATION; EVALUATION; FEEDBACK SYSTEM; METHODOLOGY; NONLINEAR SYSTEM; ROBOTICS; STATISTICAL MODEL; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMIMETICS; CEREBELLUM; COMPUTER SIMULATION; FEEDBACK; MODELS, STATISTICAL; MODELS, THEORETICAL; NONLINEAR DYNAMICS; PATTERN RECOGNITION, AUTOMATED; ROBOTICS;

EID: 34249071319     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2006.888761     Document Type: Article

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