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Sliding-Mode Fuzzy Controllers

  • Shows how increasingly popular sliding-mode control techniques can be integrated with adaptive fuzzy techniques
  • Brings together methods scattered through the literature and provides an in-depth comparison of their pros and cons
  • Includes MATLAB® and Simulink® codes which allow the reader to simulate controllers described in the book

Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 357)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xvi
  2. Preliminaries

    • Mojtaba Ahmadieh Khanesar, Okyay Kaynak, Erdal Kayacan
    Pages 1-22
  3. Classical Sliding-Mode Controllers

    • Mojtaba Ahmadieh Khanesar, Okyay Kaynak, Erdal Kayacan
    Pages 23-56
  4. Fuzzy Logic Systems

    • Mojtaba Ahmadieh Khanesar, Okyay Kaynak, Erdal Kayacan
    Pages 57-87
  5. Rule-Based Sliding-Mode Fuzzy Logic Control

    • Mojtaba Ahmadieh Khanesar, Okyay Kaynak, Erdal Kayacan
    Pages 89-102
  6. Adaptive Sliding-Mode Fuzzy Control Systems: Gradient Descent Method

    • Mojtaba Ahmadieh Khanesar, Okyay Kaynak, Erdal Kayacan
    Pages 103-124
  7. Adaptive Sliding-Mode Fuzzy Control Systems: Lyapunov Approach

    • Mojtaba Ahmadieh Khanesar, Okyay Kaynak, Erdal Kayacan
    Pages 125-178
  8. Adaptive Network Sliding-Mode Fuzzy Logic Control Systems

    • Mojtaba Ahmadieh Khanesar, Okyay Kaynak, Erdal Kayacan
    Pages 179-202
  9. Sliding-Mode Fuzzy Logic Teleoperation Controllers

    • Mojtaba Ahmadieh Khanesar, Okyay Kaynak, Erdal Kayacan
    Pages 203-212
  10. Intelligent Optimization of Sliding-Mode Fuzzy Logic Controllers

    • Mojtaba Ahmadieh Khanesar, Okyay Kaynak, Erdal Kayacan
    Pages 213-234
  11. Back Matter

    Pages 235-237

About this book

This book addresses some of the challenges suffered by the well-known and robust sliding-mode control paradigm. The authors show how the fusion of fuzzy systems with sliding-mode controllers can alleviate some of these problems and promote applicability.

Fuzzy systems used as soft switches eliminate high-frequency signal oscillations and can substantially lower the noise sensitivity of sliding-mode controllers. The amount of a priori knowledge required concerning the nominal structure and parameters of a nonlinear system is also shown to be much reduced by exploiting the general function-approximation property of fuzzy systems so as to use them as identifiers.

 The main features of this book include:

• a review of various existing structures of sliding-mode fuzzy control;

• a guide to the fundamental mathematics of sliding-mode fuzzy controllers and their stability analysis;

• state-of-the-art procedures for the design of a sliding-mode fuzzy controller;

• source codes including MATLAB® and Simulink® codes illustrating the simulation of these controllers, particularly the adaptive controllers;

• a short bibliography for each chapter for readers interested in learning more on a particular subject; and

• illustrative examples and simulation results to support the main claims made in the text.

Academic researchers and graduate students interested in the control of nonlinear systems and particularly those working in sliding-mode controller design will find this book a valuable source of comparative information on existing controllers and ideas for the development of new ones.

Authors and Affiliations

  • Faculty of Engineering, University of Nottingham, Nottingham, UK

    Mojtaba Ahmadieh Khanesar

  • Department of Electrical and Electronics Engineering, Bogazici University, Istanbul, Turkey

    Okyay Kaynak

  • Department of Electrical and Computer Engineering, Aarhus University, Aarhus, Denmark

    Erdal Kayacan

About the authors

Doctor Mojtaba Ahmadieh Khanesar received the M.S. and Ph.D. degree in Control Engineering from K. N. Toosi University of Technology, Tehran, Iran, in 2007 and 2012, respectively.

In 2010, he has held a 9-month visiting student position at Bogazici University, Istanbul, Turkey. He is currently Assistant Professor in the Control and Electrical Engineering Department, Semnan University, Semnan, Iran. His current research interests are sliding-mode control, adaptive controller design, fuzzy systems and intelligent optimization. 

Okyay Kaynak received the B.Sc. (first-class honors) and Ph.D. degrees in electronic and electrical engineering from the University of Birmingham, U.K., in 1969 and 1972, respectively. From 1972 to 1979, he held various positions within the industry. In 1979, he joined the Department of Electrical and Electronics Engineering, Bogazici University, Istanbul, Turkey, where he is presently an Emeritus Professor. He also holds a "1000 Talents Program" Professor title at the University of Science and Technology, Beijing, China. He has hold long-term (near to or more than a year) Visiting Professor/Scholar positions at various institutions in Japan, Germany, U.S., Singapore, and China. His current main research interest is in the broad field of intelligent control. He has authored three books and edited five and authored or coauthored more than 400 papers that have appeared in various journals, books, and conference proceedings. He has been in the editorial boards of several journals. Currently, he is the Editor-in-Chief of the Springer journal; Discover Artificial Intelligence. Additionally, the Springer volume "Recent Advances in Sliding Modes: From Control to Intelligent Mechatronics" is dedicated to him to commemorate his lifetime impactful research and scholarly achievements and outstanding services to profession.

Dr. Kaynak is a fellow of IEEE. He has served on many committees of IEEE and was the president of IEEE Industrial Electronics Society during 2002-2003..

Erdal Kayacan received a Ph.D. degree in electrical and electronic engineering at Bogazici University, Istanbul, Turkey, in 2011. After finishing his postdoctoral research in KU Leuven at the division of mechatronics, biostatistics and sensors (MeBioS) in 2014, he worked in Nanyang Technological University, Singapore, at the School of Mechanical and Aerospace Engineering as Assistant Professor for four years. Currently, he is pursuing his research at Aarhus University at the Department of Engineering as Associate Professor.

He has since published more than 110 peer-refereed book chapters, journal and conference papers in model-based and model-free control, parameter and state estimation, and their robotics applications.  He has completed a number of research projects which have focused on the design and development of ground and aerial robotic systems, vision-based control techniques and artificialintelligence. Dr. Kayacan is the co-writer of a course book “Fuzzy Neural Networks for Real Time Control Applications, 1st Edition Concepts, Modeling and Algorithms for Fast Learning.”He is Senior Member of Institute of Electrical and Electronics Engineers (IEEE). Since 1st January 2017, he is Associate Editor of IEEE Transactions on Fuzzy Systems and IEEE Transactions on Mechatronics.


Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access