NLq Theory: A neural control framework with global asymptotic stability criteria

Neural Networks

Volumn 10, Issue 4, 1997, Pages 615-637

  Suykens, Johan A K ^a,b   De Moor, Bart L R ^a   Vandewalle, Joos ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b Katholieke Universiteit Leuven   (Belgium)

Author keywords

Dissipativity; Dynamic backpropagation; Global asymptotic stability; Input output stability; Linear matrix inequalities; Lyapunov function; Multilayer recurrent neutral networks; Neural control; State space models

Indexed keywords

ASYMPTOTIC STABILITY; BACKPROPAGATION; CLOSED LOOP CONTROL SYSTEMS; CONTROL SYSTEM SYNTHESIS; LYAPUNOV METHODS; MATHEMATICAL MODELS; MATRIX ALGEBRA; NONLINEAR CONTROL SYSTEMS; ROBUSTNESS (CONTROL SYSTEMS); STATE SPACE METHODS; SYSTEM STABILITY;

LINEAR MATRIX INEQUALITIES; MULTILAYER RECURRENT NEURAL NETWORK; NEURAL CONTROL;

FEEDFORWARD NEURAL NETWORKS;

ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; CALCULATION; LEARNING; MATHEMATICAL ANALYSIS; PRIORITY JOURNAL; THEORY;

EID: 0031170885     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0893-6080(96)00104-9     Document Type: Article

References (6)

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