Adaptive predictive control using neural network for a class of pure-feedback systems in discrete time

IEEE Transactions on Neural Networks

Volumn 19, Issue 9, 2008, Pages 1599-1614

  Ge, Shuzhi Sam ^a   Yang, Chenguang ^a   Lee, Tong Heng ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Discrete time system; Neural network; Pure feedback system

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; ADAPTIVE SYSTEMS; CONTINUOUS TIME SYSTEMS; CONTROL SYSTEMS; DIGITAL CONTROL SYSTEMS; DISCRETE TIME CONTROL SYSTEMS; FEEDBACK; FEEDBACK CONTROL; IMAGE CLASSIFICATION; NEURAL NETWORKS; SYSTEM STABILITY;

ADAPTIVE NEURAL NETWORKS; ADAPTIVE PREDICTIVE CONTROL; CLOSED-LOOP SYSTEMS; CONTROL APPROACHES; CONTROL DESIGNS; CONTROL INPUTS; DISCRETE TIME; DISCRETE-TIME SYSTEM; DISCRETE-TIME SYSTEMS; FEEDBACK SYSTEMS; IMPLICIT FUNCTION THEOREM; INPUT-OUTPUT; NEURAL NETWORK; NN CONTROL; OUTPUT FEEDBACK CONTROLS; OUTPUT TRACKING; PREDICTION FUNCTIONS; PURE-FEEDBACK SYSTEM; SIMULATION RESULTS; UNIFORM ULTIMATE BOUNDEDNESS;

STATE FEEDBACK;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; FEEDBACK SYSTEM; METHODOLOGY; SIGNAL PROCESSING; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; FEEDBACK; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 52149102489     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2008.2000446     Document Type: Article

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