Neural controller design-based adaptive control for nonlinear MIMO systems with unknown hysteresis inputs

IEEE Transactions on Cybernetics

Volumn 46, Issue 1, 2016, Pages 9-19

  Liu, Yan Jun ^a   Tong, Shaocheng ^a   Chen, C L Philip ^b   Li, Dong Juan ^a  

^a LIAONING UNIVERSITY OF TECHNOLOGY   (China)

^b UNIVERSITY OF MACAU   (Macao)

Author keywords

Adaptive control; Intelligent control; Neural networks (NNs); Nonlinear control theory; Prandtl Ishlinskii (PI) hysteresis inputs

Indexed keywords

BACKSTEPPING; CLOSED LOOP SYSTEMS; COMMUNICATION CHANNELS (INFORMATION THEORY); CONTROLLERS; HYSTERESIS; MIMO SYSTEMS; RADIAL BASIS FUNCTION NETWORKS; TELECOMMUNICATION NETWORKS;

ADAPTIVE NEURAL CONTROL; BACKSTEPPING TECHNIQUE; HYSTERESIS MODELING; MULTIPLE INPUT MULTIPLE OUTPUT SYSTEM; NEURAL CONTROLLER; NONLINEAR MIMO SYSTEMS; RADIAL BASIS FUNCTIONS NEURAL NETWORKS; SIMULATION EXAMPLE;

ADAPTIVE CONTROL SYSTEMS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; NONLINEAR SYSTEM; THEORETICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS;

EID: 84960416445     PISSN: 21682267     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCYB.2015.2388582     Document Type: Article

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