A Levenberg-Marquardt learning applied for recurrent neural identification and control of a wastewater treatment bioprocess

International Journal of Intelligent Systems

Volumn 24, Issue 11, 2009, Pages 1094-1114

  Baruch, Ieroham S ^a   Mariaca Gaspar, Carlos R ^a  

^a DEPARTAMENTO DE FÍSICA   (Mexico)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE TRAJECTORY; ESTIMATED STATE; INDIRECT ADAPTIVE CONTROL; LEVENBERG-MARQUARDT; MEAN SQUARED ERROR; NEURAL IDENTIFICATION; NOISE FILTERING; NONLINEAR PLANT; PLANT OUTPUT; REFERENCE-TRACKING; SLIDING MODE CONTROLLER; SYSTEMS IDENTIFICATION; WASTEWATER TREATMENT BIOPROCESS;

BACKPROPAGATION ALGORITHMS; CONVERGENCE OF NUMERICAL METHODS; INTELLIGENT SYSTEMS; LEARNING SYSTEMS; PARAMETER ESTIMATION; REAL TIME CONTROL; RECURRENT NEURAL NETWORKS; WASTEWATER; WASTEWATER RECLAMATION; WASTEWATER TREATMENT; WATER TREATMENT PLANTS;

LEARNING ALGORITHMS;

EID: 70349592179     PISSN: 08848173     EISSN: 1098111X     Source Type: Journal    
DOI: 10.1002/int.20377     Document Type: Article

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