Title :
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.
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;
Conference_Titel :
Industrial Technology, 2005. ICIT 2005. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-9484-4
DOI :
10.1109/ICIT.2005.1600760
