Neural-network-based state feedback control of a nonlinear discrete-time system in nonstrict feedback form

IEEE Transactions on Neural Networks

Volumn 19, Issue 12, 2008, Pages 2073-2087

  Jagannathan, Sarangapani ^a   He, Pingan ^b  

^a Architectural and Environmental Engineering   (United States)

^b GM Powertrain Group   (United States)

Author keywords

Adaptive critic control; Near optimal control; Neural network (NN) control; Nonstrict feedback system

Indexed keywords

CLOSED LOOP CONTROL SYSTEMS; CONTINUOUS TIME SYSTEMS; CONTROL SYSTEMS; DIGITAL CONTROL SYSTEMS; DISCRETE TIME CONTROL SYSTEMS; FEEDBACK; FEEDBACK CONTROL; INTERSECTIONS; NEURAL NETWORKS; OPTIMAL CONTROL SYSTEMS; STATE FEEDBACK; SYSTEM STABILITY;

ADAPTIVE CRITIC ARCHITECTURES; ADAPTIVE CRITIC CONTROL; ADAPTIVE NEURAL NETWORKS; BACKSTEPPING DESIGNS; CLOSED-LOOP CONTROLS; CONTROL INPUTS; CONTROLLER DESIGNS; FEEDFORWARD; LOOP STABILITIES; NEAR-OPTIMAL CONTROL; NEURAL NETWORK (NN) CONTROL; NN CONTROLS; NONLINEAR DISCRETE-TIME SYSTEMS; NONSTRICT FEEDBACK SYSTEM; OFFLINE LEARNINGS; STABILITY ANALYSES; STATE FEEDBACK CONTROLS; TRACKING ERRORS; TRACKING PERFORMANCES; UTILITY FUNCTIONS;

ADAPTIVE CONTROL SYSTEMS;

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

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

EID: 57749111482     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2008.2003295     Document Type: Article

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