Robust Control Systems with Genetic Algorithms
eBook - ePub

Robust Control Systems with Genetic Algorithms

  1. 232 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Robust Control Systems with Genetic Algorithms

About this book

In recent years, new paradigms have emerged to replace-or augment-the traditional, mathematically based approaches to optimization. The most powerful of these are genetic algorithms (GA), inspired by natural selection, and genetic programming, an extension of GAs based on the optimization of symbolic codes.

Robust Control Systems with Genetic Algorithms builds a bridge between genetic algorithms and the design of robust control systems. After laying a foundation in the basics of GAs and genetic programming, it demonstrates the power of these new tools for developing optimal robust controllers for linear control systems, optimal disturbance rejection controllers, and predictive and variable structure control. It also explores the application of hybrid approaches: how to enhance genetic algorithms and programming with fuzzy logic to design intelligent control systems. The authors consider a variety of applications, such as the optimal control of robotic manipulators, flexible links and jet engines, and illustrate a multi-objective, genetic algorithm approach to the design of robust controllers with a gasification plant case study.

The authors are all masters in the field and clearly show the effectiveness of GA techniques. Their presentation is your first opportunity to fully explore this cutting-edge approach to robust optimal control system design and exploit its methods for your own applications.

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Yes, you can access Robust Control Systems with Genetic Algorithms by Mo Jamshidi,Renato A. Krohling,Leandro dos S. Coelho,Peter J. Fleming in PDF and/or ePUB format, as well as other popular books in Computer Science & Electrical Engineering & Telecommunications. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Dedication
  7. Preface
  8. Table of Contents
  9. Chapter One: Genetic algorithms
  10. Chapter Two: Optimal robust control
  11. Chapter Three: Methods for controller design using genetic algorithms*
  12. Chapter Four: Predictive and variable structure control designs
  13. Chapter five: Design methods, simulation results, and conclusion
  14. Chapter Six: Tuning fuzzy logic controllers for robust control system design
  15. Chapter Seven: GA-fuzzy hierarchical control design approach*
  16. Chapter Eight: Autonomous robot navigation through fuzzygenetic programming*
  17. Chapter Nine: Robust control system design: A hybrid H-infinity/multiobjective optimization approach
  18. Appendix A
  19. Index