Optimal Fuzzy Self-Tuning of PI Controller Using Genetic Algorithm for Induction Motor Speed Control
Ismail K. Bouserhane*,**, Abdeldjebar Hazzab*,
Abdelkrim Boucheta*, Benyounes Mazari**, and Rahli Mostefa**
*University Center of Bechar, B.P 417 Bechar 08000, Algeria
**Laboratoire de Développement et des Entraînements Electriques LDEE, University of Sciences and Technology of Oran, B.P 1523 El-M’naouer (31000), Oran, Algeria
We present induction motor speed control using optimal PI controller fuzzy gain scheduling. To improve PI controller performance, we designed fuzzy PI controller gain tuning for indirect-field oriented IMspeed control using fuzzy rules on-line to adapt PI controller parameters based on error and its first time derivative. To overcome the major disadvantage of fuzzy logic control, i.e., the lack of design technique, we propose optimization of fuzzy logic tuning parameters using a genetic algorithm. Optimally designed fuzzy logic provides suitable PI controller gain to achieve the desired speed while varying load torque and parameters. Simulation demonstrated the performance of the proposed optimal fuzzy-logic tuning PI controller, and numerical validation results of our proposal showed performance comparable to a fuzzy controller having parameters chosen by a human operator.
Abdelkrim Boucheta, Benyounes Mazari, and Rahli Mostefa, “Optimal Fuzzy Self-Tuning of PI Controller Using Genetic Algorithm for Induction Motor Speed Control,” Int. J. Automation Technol., Vol.2, No.2, pp. 85-95, 2008.
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