Neuro-Control and its Applications

1. Front Matter

   Pages i-xiii

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2. Introduction

   • Sigeru Omatu, Marzuki Khalid, Rubiyah Yusof

   Pages 1-6

3. Neural Networks

   • Sigeru Omatu, Marzuki Khalid, Rubiyah Yusof

   Pages 7-27

4. Traditional Control Schemes

   • Sigeru Omatu, Marzuki Khalid, Rubiyah Yusof

   Pages 29-83

5. Neuro-Control Techniques

   • Sigeru Omatu, Marzuki Khalid, Rubiyah Yusof

   Pages 85-170

6. Neuro-Control Applications

   • Sigeru Omatu, Marzuki Khalid, Rubiyah Yusof

   Pages 171-243

7. Back Matter

   Pages 245-255

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The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies, ........... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advance collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Sigeru Omatu, Marzuki Khalid, and Rubiyah Yusof have pursued the new developments of fuzzy logic and neural networks to present a series volume on neuro-control methods. As they demonstrate in the opening pages of their book, there is an explosion of interest in this field. Publication and patent activity in these areas are ever growing according to international is timely. databases and hence, this volume The presentation of the material follows a complementary pattern. Reviews of existing control techniques are given along side an exposition of the theoretical constructions of fuzzy logic controllers, and controllers based on neural networks. This is an extremely useful methodology which yields rewards in the applications chapters. The series of applications includes one very thorough experimental sequence for the control of a hot-water bath.

• control
• control system
• fuzzy logic
• fuzzy set
• fuzzy system
• intelligent control
• neural networks
• nonlinear control
• optimal control
• optimization
• pid control
• pid controller
• real-time control
• simulation
• stabilization

• Department of Computer and Systems Sciences, College of Engineering, Osaka Prefecture University, Sakai, Osaka 593, Japan

  Sigeru Omatu

• Business and Advanced Technology Centre, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

  Marzuki Khalid, Rubiyah Yusof

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