Intelligent Control

A Hybrid Approach Based on Fuzzy Logic, Neural Networks and Genetic Algorithms

  • Nazmul Siddique

Part of the Studies in Computational Intelligence book series (SCI, volume 517)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Nazmul Siddique
    Pages 1-9
  3. Nazmul Siddique
    Pages 11-37
  4. Nazmul Siddique
    Pages 39-55
  5. Nazmul Siddique
    Pages 57-93
  6. Nazmul Siddique
    Pages 95-135
  7. Nazmul Siddique
    Pages 137-178
  8. Nazmul Siddique
    Pages 179-216
  9. Nazmul Siddique
    Pages 217-242
  10. Nazmul Siddique
    Pages 243-267
  11. Nazmul Siddique
    Pages 269-280
  12. Back Matter
    Pages 281-282

About this book

Introduction

Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.  The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined.

The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area.

Intelligent Control will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control.

Keywords

Evolutionary Algorithm Fuzzy Control Hybrid Systems Intelligent Control Neural Networks

Authors and affiliations

  • Nazmul Siddique
    • 1
  1. 1.School of Computing and Intelligent SystemsUniversity of UlsterLondonderryUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-02135-5
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-02134-8
  • Online ISBN 978-3-319-02135-5
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book
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