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http://dx.doi.org/10.5207/JIEIE.2011.25.5.022

Hybrid Fuzzy Controller for DTC of Induction Motor Drive  

Ko, Jae-Sub (순천대학교 전기제어공학과)
Choi, Jung-Sik (전자부품연구원)
Chung, Dong-Hwa (순천대학교 정보통신공학부)
Publication Information
Journal of the Korean Institute of Illuminating and Electrical Installation Engineers / v.25, no.5, 2011 , pp. 22-33 More about this Journal
Abstract
An induction motor operated with a conventional direct self controller(DSC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic controller(FLC) is used in conjection with DSC to minimize these problems. A FLC chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determinated by observing the vector diagram of flux and currents. This paper proposes hybrid fuzzy controller for direct torque control(DTC) of induction motor drives. The speed controller is based on adaptive fuzzy learning controller(AFLC), which provide high dynamics performances both in transient and steady state response. Flux position, error in flux magnitude and error in torque are used as FLC state variables. The speed is estimated with model reference adaptive system(MRAS) based on artificial neural network(ANN) trained on-line by a back-propagation algorithm. This paper is controlled speed using hybrid fuzzy controller(HFC) and estimation of speed using ANN. The performance of the proposed induction motor drive with HFC controller and ANN is verified by analysis results at various operation conditions.
Keywords
Induction Motor Drive; DTC; HFC; AFLC; Speed Estimation;
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