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Modern Adaptive Fuzzy Control Systems

  • Book
  • © 2023

Overview

Authors:
  1. Ardashir Mohammadzadeh

    1. Multidisciplinary Center for Infrastructure Engineering (MCIE), Shenyang University of Technology, Shenyang, China

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  2. Mohammad Hosein Sabzalian

    1. LabREI—Smart Grid Laboratory, Department of Systems and Energy, FEEC—School of Electrical and Computer Engineering, University of Campinas (UNICAMP), Campinas, Brazil

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  3. Chunwei Zhang

    1. Multidisciplinary Center for Infrastructure Engineering (MCIE), Shenyang University of Technology, Shenyang, China

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  4. Oscar Castillo

    1. Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico

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  5. Rathinasamy Sakthivel

    1. Department of Applied Mathematics, Bharathiar University, Coimbatore, India

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  6. Fayez F. M. El-Sousy

    1. Department of Electrical Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al Kharj, Saudi Arabia

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  • Practically explains fuzzy systems and different methods of training and optimizing these systems
  • Demonstrates the analysis and optimization of type-2 neuro-fuzzy systems
  • Presents all well-known optimization methods clearly and shows how to code them in MATLAB

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 421)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. An Introduction to Fuzzy and Fuzzy Control Systems

    • Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy
    Pages 1-3

  3. Classification of Adaptive Fuzzy Controllers

    • Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy
    Pages 5-16

  4. Type-2 Fuzzy Systems

    • Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy
    Pages 17-47

  5. Training Interval Type-2 Fuzzy Systems Based on Error Backpropagation

    • Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy
    Pages 49-93

  6. Baseline Indirect Adaptive Control

    • Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy
    Pages 95-102

  7. Type-2 Indirect Adaptive Control with Estimation Error Approximation

    • Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy
    Pages 103-117

  8. Direct Adaptive Fuzzy Control

    • Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy
    Pages 119-133

  9. Direct Adaptive Fuzzy Control with a Self-regulated Structure

    • Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy
    Pages 135-144

  10. State Limitation Through Supervised Control

    • Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy
    Pages 145-149

  11. Adaptive Sliding Fuzzy Control

    • Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy
    Pages 151-157
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Keywords

About this book

This book explains the basic concepts, theory and applications of fuzzy systems in control in a simple unified approach with clear ex-amples and simulations in the MATLAB programming language. Fuzzy systems, especially, type-2 neuro-fuzzy systems, are now used extensively in various engineering fields for different purposes. In plain language, this book aims to practically explain fuzzy sys-tems and different methods of training and optimizing these systems. For this purpose, type-2 neuro-fuzzy systems are first analyzed along with various methods of training and optimizing these systems through implementation in MATLAB. These systems are then em-ployed to design adaptive fuzzy controllers. The authors aim at pre-senting all the well-known optimization methods clearly and code them in the MATLAB language.

Authors and Affiliations

  • Multidisciplinary Center for Infrastructure Engineering (MCIE), Shenyang University of Technology, Shenyang, China

    Ardashir Mohammadzadeh, Chunwei Zhang

  • LabREI—Smart Grid Laboratory, Department of Systems and Energy, FEEC—School of Electrical and Computer Engineering, University of Campinas (UNICAMP), Campinas, Brazil

    Mohammad Hosein Sabzalian

  • Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

  • Department of Applied Mathematics, Bharathiar University, Coimbatore, India

    Rathinasamy Sakthivel

  • Department of Electrical Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al Kharj, Saudi Arabia

    Fayez F. M. El-Sousy

Bibliographic Information

  • Book Title: Modern Adaptive Fuzzy Control Systems

  • Authors: Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy

  • Series Title: Studies in Fuzziness and Soft Computing

  • DOI: https://doi.org/10.1007/978-3-031-17393-6

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Hardcover ISBN: 978-3-031-17392-9Published: 03 November 2022

  • Softcover ISBN: 978-3-031-17395-0Published: 04 November 2023

  • eBook ISBN: 978-3-031-17393-6Published: 02 November 2022

  • Series ISSN: 1434-9922

  • Series E-ISSN: 1860-0808

  • Edition Number: 1

  • Number of Pages: X, 157

  • Number of Illustrations: 4 b/w illustrations, 91 illustrations in colour

  • Topics: Computational Intelligence, Control and Systems Theory, Artificial Intelligence

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