Genetic algorithm based fast speed response induction motor drive with ANN flux estimator

Author

Rafiq, Md Abdur ; Sarwer, Mohammed Golam ; Datta, Manoj ; Ghosh, B.C.

Author_Institution

Dept. of Electr. & Electron. Eng., Khulna Univ. of Eng. & Technol.

fYear

2005

fDate

14-17 Dec. 2005

Firstpage

882

Lastpage

887

Abstract

This paper presents a genetic algorithm based controller for poly-phase induction motor drive. The proportional and integral gain of PI controller is optimized by genetic algorithm. An adaptive recurrent neural network (RNN) is proposed to estimate the stator and rotor fluxes. An online tuning scheme to update the weight of RNN is presented to overcome stator resistance variation problem. This tuning scheme requires current sensor to calculate the current error. Simulation tests have been performed to study the dynamic performances of the drive system for both the classical PI and the genetic algorithm based controllers

Keywords

PI control; control engineering computing; electric machine analysis computing; electric sensing devices; genetic algorithms; induction motor drives; machine control; machine testing; recurrent neural nets; rotors; stators; ANN flux estimator; PI controller; current error calculation; current sensor; genetic algorithm; online tuning scheme; polyphase induction motor drive; proportional and integral gain; recurrent neural network; rotor fluxes; stator estimation; stator resistance variation problem; Adaptive systems; Artificial neural networks; Genetic algorithms; Induction motor drives; Performance evaluation; Pi control; Proportional control; Recurrent neural networks; Rotors; Stators; Genetic algorithm; induction motor; recurrent neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Technology, 2005. ICIT 2005. IEEE International Conference on

Conference_Location

Hong Kong

Print_ISBN

0-7803-9484-4

Type

conf

DOI

10.1109/ICIT.2005.1600760

Filename

1600760