Title: High performance speed tracking of induction motor drives using an adaptive fuzzy-neural network control
Authors: Mokhtar Zerikat, Soufyane Chekroun
Addresses: Department of electrical engineering, ENSET, BP.1523 El Mnaouer, Oran 31000, Algeria. ' Department of electrical engineering, ENSET, BP.1523 El Mnaouer, Oran 31000, Algeria
Abstract: This paper relates an adaptive speed control of hybrid fuzzy-neural network for high-performance induction motor drives. The speed control performance of induction motors is affected by parameter variations and non-linearities in the induction motor. The aim of the proposed control scheme is to improve the performance and robustness of the induction motor drives under non-linear loads and parameter variations. Both the design of the fuzzy controller and its integration with neural networks in a global control system are discussed. The simulation results showed excellent tracking performance of the proposed control system, and have convincingly demonstrated the usefulness of the hybrid fuzzy-neural controller in high-performance drives with uncertainty.
Keywords: induction motors; hybrid control; adaptive control; robustness; fuzzy logic; fuzzy control; neural networks; neuro-fuzzy control; speed control; simulation; high-performance drives; uncertainty.
International Journal of Artificial Intelligence and Soft Computing, 2010 Vol.2 No.3, pp.231 - 244
Published online: 17 Feb 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article