Quantum Evolutionary Algorithm based fast speed controlled induction motor drive with CRTRL flux estimator

Author

Habibullah, Md ; Hossain, Md Amjad ; Rafiq, Md Abdur ; Ghosh, B.C.

Author_Institution

Dept. of Electr. & Electron. Eng., Khulna Univ. of Eng. & Technol. (KUET), Khulna, Bangladesh

fYear

2010

fDate

18-20 Dec. 2010

Firstpage

478

Lastpage

481

Abstract

This paper proposes the Quantum Evolutionary Algorithm (QEA) based fast speed response controller tuning for induction motor drive. Here the proportional and integral gains of PI controller are optimized by QEA to achieve quick speed response. A simple rotor flux estimator based on Correlated Real Time Recurrent Learning (CRTRL) algorithm is proposed for high performance induction motor drive. Simulation tests have been conducted to study the dynamic performances of the drive system for both the Conventional Genetic Algorithm (CGA) based PI and QEA based PI controllers. The proposed method shows better control performance than CGA based induction motor drive under transient and steady state conditions.

Keywords

PI control; angular velocity control; genetic algorithms; induction motor drives; learning (artificial intelligence); parameter estimation; quantum computing; recurrent neural nets; rotors; CGA; CRTRL; PI controller; QEA; conventional genetic algorithm; correlated real time recurrent learning; induction motor drive; quantum evolutionary algorithm; rotor flux estimator; speed control; Quantum evolutionary algorithm; conventional genetic algorithm; correlated real time recurrent learning; fitness function; flux estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering (ICECE), 2010 International Conference on

Conference_Location

Dhaka

Print_ISBN

978-1-4244-6277-3

Type

conf

DOI

10.1109/ICELCE.2010.5700733

Filename

5700733