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  • Book
  • © 2001

Soft Computing for Control of Non-Linear Dynamical Systems

  • Mathematical concepts are used in combination with soft computing techniques to realize robust and adaptive control of dynamical systems
  • Presentation of the latest achievements in combining soft computing techniques and their applications

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 63)

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xvi
  2. Introduction to Control of Non-Linear Dynamical Systems

    • Oscar Castillo, Patricia Melin
    Pages 1-4
  3. Fuzzy Logic

    • Oscar Castillo, Patricia Melin
    Pages 5-27
  4. Neural Networks for Control

    • Oscar Castillo, Patricia Melin
    Pages 29-62
  5. Genetic Algorithms and Simulated Annealing

    • Oscar Castillo, Patricia Melin
    Pages 63-84
  6. Dynamical Systems Theory

    • Oscar Castillo, Patricia Melin
    Pages 85-103
  7. Hybrid Intelligent Systems for Time Series Prediction

    • Oscar Castillo, Patricia Melin
    Pages 105-117
  8. Intelligent Control of Robotic Dynamic Systems

    • Oscar Castillo, Patricia Melin
    Pages 149-162
  9. Controlling Biochemical Reactors

    • Oscar Castillo, Patricia Melin
    Pages 163-174
  10. Controlling Aircraft Dynamic Systems

    • Oscar Castillo, Patricia Melin
    Pages 175-185
  11. Controlling Electrochemical Processes

    • Oscar Castillo, Patricia Melin
    Pages 187-196
  12. Controlling International Trade Dynamics

    • Oscar Castillo, Patricia Melin
    Pages 197-208
  13. Back Matter

    Pages 209-221

About this book

This book presents a unified view of modelling, simulation, and control of non­ linear dynamical systems using soft computing techniques and fractal theory. Our particular point of view is that modelling, simulation, and control are problems that cannot be considered apart, because they are intrinsically related in real world applications. Control of non-linear dynamical systems cannot be achieved if we don't have the appropriate model for the system. On the other hand, we know that complex non-linear dynamical systems can exhibit a wide range of dynamic behaviors ( ranging from simple periodic orbits to chaotic strange attractors), so the problem of simulation and behavior identification is a very important one. Also, we want to automate each of these tasks because in this way it is more easy to solve a particular problem. A real world problem may require that we use modelling, simulation, and control, to achieve the desired level of performance needed for the particular application.

Authors and Affiliations

  • Department of Computer Science, Tijuana Institute of Technology, Chula Vista, USA

    Oscar Castillo, Patricia Melin

Bibliographic Information

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access