High performance speed tracking of induction motor drives using an adaptive fuzzy-neural network control. (18th February 2011)

• Record Type: Journal Article
• Authors: Zerikat, Mokhtar; Chekroun, Soufyane
• Is Part Of: International journal of artificial intelligence and soft computing. Volume 2:Number 3(2010)
• Page Start: 231
• Page End: 244
• Publication Date: 2011-02-18
• Subjects: induction motors -- hybrid control -- adaptive control -- robustness -- fuzzy logic -- fuzzy control -- neural networks -- neuro-fuzzy control -- speed control -- simulation -- high-performance drives -- uncertainty; Artificial intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-4950

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.