Review and Investigation of Simplified Rules Fuzzy Logic Speed Controller of High Performance Induction Motor Drives

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Date

2020

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Volume Title

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

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GOLD

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No

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Abstract

The use of Fuzzy Logic Controller (FLC) as a speed controller for Induction Motor (IM) drives is garnering strong researchers' interest since it has proven to achieve superior performance compared to conventional controllers. The aim of this study is to review and investigate the design, operations, and effects of rules reduction for FLC in IM drives. Based on the literature, the most commonly used technique to design FLC Membership Functions (MFs) rule-base and control model is based on engineering skills and experienced behavioral aspects of the controlled system. Simplified fuzzy rules approaches have been introduced to reduce the number of fuzzy rules in order to realize hardware implementation. This study discusses different simplified rules methods applied to IM drives. Most of the proposed methods shared a common drawback in that they lacked systematic procedures for designing FLC rule base. Therefore, this research proposed a methodological approach to designing and simplifying the FLC rule-base for IM drives based on dynamic step response and phase plane trajectory of the second order representation of IM drives systems. The proposed method presents guidance for designing FLC rule-base based on the general dynamic step response of the controlled system. Following the proposed method procedures, a (9, 25, 49) rules size has been designed and simplified to a (5, 7, 9) rules size. The effectiveness and accuracy of the designed rules as well as the simplified rules were verified by conducting simulation analysis of IM drives using MATLAB/Simulink environment. Step speed command performance comparisons were achieved with both standard designed and simplified rules at various speed demands. The simulation results showed that the simplified rules maintain the drive performance and produced similar behavior as the standard designed rules.

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Keywords

Fuzzy Logic, Fuzzy Sets, Mathematical Model, Control Systems, Rotors, Stators, Hardware, Flc, Im Drives, Simplified Rules, Rule-Base, Step Response, Phase-Plane, Systematic, Field-Oriented Control, Direct Torque Control, Indirect Vector Control, Control-Systems, Pi Controllers, Reduction, Optimization, Interval, Design, Identification, Artificial intelligence, Astronomy, FOS: Political science, Trajectory, Adaptive Control, Engineering, Interval Type-2 Fuzzy Logic, step response, Fuzzy Rule-Based Systems, Neuro-Fuzzy Methods, Induction motor, Fuzzy Logic Systems, Political science, Base (topology), Control engineering, Physics, Politics, IM drives, FLC, Physical Sciences, Electrical engineering. Electronics. Nuclear engineering, MATLAB, Control (management), FOS: Law, phase-plane, Mathematical analysis, Artificial Intelligence, Analysis of Electric Machinery and Drive Systems, FOS: Electrical engineering, electronic engineering, information engineering, Control theory (sociology), FOS: Mathematics, Type-2 Fuzzy Logic Systems and Applications, Electrical and Electronic Engineering, Biology, rule-base, Controller (irrigation), Voltage, Fuzzy rule, Neural Network Fundamentals and Applications, Computer science, Agronomy, TK1-9971, Fuzzy logic, Operating system, Fuzzy control system, Electrical engineering, Computer Science, simplified rules, Representation (politics), Law, Mathematics

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Fields of Science

02 engineering and technology, 0202 electrical engineering, electronic engineering, information engineering

Citation

WoS Q

Q2

Scopus Q

Q1
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OpenCitations Citation Count
46

Source

IEEE ACCESS

Volume

8

Issue

Start Page

49377

End Page

49394
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CrossRef : 12

Scopus : 67

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Mendeley Readers : 100

SCOPUS™ Citations

66

checked on Feb 03, 2026

Web of Science™ Citations

43

checked on Feb 03, 2026

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