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An Artificial Neural Network for Online Tuning of Genetic Algorithm Based PI Controller for Interior Permanent Magnet Synchronous Motor–Drive

Rahman, M. A. and Nasir Uddin, M. and Abido, M. A. (2006) An Artificial Neural Network for Online Tuning of Genetic Algorithm Based PI Controller for Interior Permanent Magnet Synchronous Motor–Drive. Canadian Journal of Electrical and Computer Engineering, 31 (3). pp. 159-165.

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Abstract

An artificial neural network (ANN) for online tuning of a genetic algorithm based PI controller for interior permanent magnet synchronous motor (IPMSM) drive is presented in this paper. The proposed controller is developed for accurate speed control of the IPMSM drive under system disturbances. In this work, initially different operating conditions are obtained based on motor dynamics incorporating various uncertainties. At each operating condition a genetic algorithm (GA) is used to optimize proportional-integral (PI) controller parameters in a closed loop vector control scheme. In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A radial basis function network (RBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed controller is successfully implemented in real-time using a digital signal processor board DS1102 for a laboratory 1 hp IPMSM. The efficacy of the proposed controller is verified by simulation as well as experimental results at different dynamic operating conditions. The proposed approach is found to be a robust controller for application in the IPMSM drive



Item Type:Article
Date:2006
Date Type:Publication
Subjects:Electrical
Divisions:College Of Engineering Sciences > Electrical Engineering Dept
Creators:Rahman, M. A. and Nasir Uddin, M. and Abido, M. A.
Email:UNSPECIFIED, UNSPECIFIED, mabido@kfupm.edu.sa
ID Code:563
Deposited By:Obaid-Ur-Rehman Khattak
Deposited On:22 Mar 2008 16:12
Last Modified:12 Apr 2011 13:06

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