NDLI: A self-organizing and self-tuning fuzzy logic controller for field oriented control of induction motor drives

Content Provider	IEEE Xplore Digital Library
Author	Ashrafzadeh, F. Nowicki, E.P. Salmon, J.C.
Copyright Year	1995
Description	Author affiliation: Dept. of Electr. Eng., Calgary Univ., Alta., Canada (Ashrafzadeh, F.; Nowicki, E.P.)
Abstract	This paper proposes a design approach for a self-organizing self-tuning fuzzy logic controller, and is applied to the design of a field oriented drive system. The basic structure of a fuzzy logic controller is outlined and the design problems associated with the conventional trial-and-error schemes are addressed. The suitability of the genetic algorithm optimization technique as a means to determine and optimize the fuzzy logic controller design is discussed. In the proposed approach normalization factors and/or membership function parameters and/or the controller policy, are translated into bit-strings. These bit-strings are processed by the genetic algorithm and if the selection process as well as the objective function are chosen properly, a near-optimal solution can be found. To examine the efficiency of the proposed approach, a self-tuning and self-organizing fuzzy logic controller for an indirect field oriented induction motor drive is designed in both a sequential and a concurrent manner. A particular objective function (i.e., a performance index) is chosen to achieve a high dynamic performance. The simulation results demonstrate a significant enhancement in shortening the development time, and improving system performance over a manually tuned fuzzy logic controller.
Starting Page	1656
Ending Page	1662
File Size	575674
Page Count	7
File Format	PDF
ISBN	0780330080
ISSN	01972618
DOI	10.1109/IAS.1995.530503
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-10-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy logic Induction motor drives Algorithm design and analysis Automatic control Nonlinear control systems Control system synthesis Control systems Tuning Genetic algorithms Design optimization
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Electrical and Electronic Engineering

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