DocumentCode :
3216747
Title :
Moving horizon parameter estimation of series DC motor using genetic algorithm
Author :
Jabri, Majed ; Belgacem, Abir ; Jerbi, Houssem
Author_Institution :
Lab. d´´Etude et de Commande Autom. des Processus (LECAP), Gabes, Tunisia
fYear :
2009
fDate :
9-11 Dec. 2009
Firstpage :
1528
Lastpage :
1531
Abstract :
Fault detection and diagnosis can effect system reliability and avoid expensive maintenance. In a manufacturing process, a simple fault can lead to environmental damage. In this way, one of the most commonly applied fault detection method is the parameter estimation technique. In this paper, we present an advanced algorithm for the estimation of electrical machine parameters by combining two approaches: the first one is the analytical Moving Horizon Estimation (MHE) strategy and the second one is the Genetic algorithm.
Keywords :
DC motors; fault diagnosis; genetic algorithms; infinite horizon; parameter estimation; reliability; electrical machine parameters; fault detection; fault diagnosis; genetic algorithm; moving horizon parameter estimation; series DC motor; system reliability; Algorithm design and analysis; DC motors; Electrical fault detection; Fault detection; Fault diagnosis; Genetic algorithms; Maintenance; Manufacturing processes; Parameter estimation; Reliability; DC series motor; Fault detection; component; genetic algorithm; moving horizon; parameter estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4244-5053-4
Type :
conf
DOI :
10.1109/NABIC.2009.5393668
Filename :
5393668
Link To Document :
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