Identification of nonlinear systems with time-varying parameters using a sliding-neural network observer

Neurocomputing

Volumn 72, Issue 7-9, 2009, Pages 1611-1620

  Ahmed Ali, Tarek ^a   Kenné, Godpromesse ^b   Lamnabhi Lagarrigue, Françoise ^c  

^a ENSIETA   (France)

^b IUT FOTSO Victor   (Cameroon)

^c UNIV PARIS SUD   (France)

Author keywords

Learning algorithms; Output equivalent injection; Radial basis function; State parameter estimation; Time varying parameter

Indexed keywords

APPLICATION EXAMPLES; CONVERGENCE RATES; FINITE-TIME CONVERGENCES; HIDDEN UNITS; LYAPUNOV; OUTPUT EQUIVALENT INJECTION; RADIAL BASIS FUNCTION; SLIDING MODE THEORIES; STATE/PARAMETER ESTIMATION; TIME-VARYING PARAMETER;

ATTITUDE CONTROL; LEARNING SYSTEMS; METAL ANALYSIS; NEURAL NETWORKS; NONLINEAR SYSTEMS; PARAMETER ESTIMATION; RADIAL BASIS FUNCTION NETWORKS; TIME VARYING CONTROL SYSTEMS; TIME VARYING NETWORKS;

LEARNING ALGORITHMS;

ACCURACY; ALGORITHM; ANALYTIC METHOD; ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL PARAMETERS; NONLINEAR SYSTEM; PRIORITY JOURNAL; SIMULATION; THEORY;

EID: 61849166186     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2008.09.001     Document Type: Article

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