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