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Adaptive Neuro-Fuzzy Controller for Synchronous Motor

Authors: Abdel Ghani Aissaoui; Mohamed Abid; Ahmed Tahour; Ahmed Chaouki Megherbi;

Adaptive Neuro-Fuzzy Controller for Synchronous Motor

Abstract

This paper presents an application of Adaptive Neuro-Fuzzy (ANF) control for synchronous motor (SM) speed. The ANF has the advantages of expert knowledge of the fuzzy inference system and the learning capabilities of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANF speed controller realizes a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of load disturbances. The results of applying the adaptive neuro-fuzzy controller to a SM give better performance and high robustness than those obtained by the application of a conventional controller.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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