Robust Control Systems with Genetic Algorithms

This text links genetic algorithms (GAs) 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 tools for developing optimal robust controllers for linear control systems, optimal disturbance rejection controllers, and predictive and variable structure control. It also explores the use of hybrid approaches that incorporate fuzzy logic into designs for intelligent control systems. The authors consider a variety of applications, such as robotic manipulators, flexible links, and jet engines, and illustrate a multi-objective GA approach using a case study.

List of contents

Genetic Algorithms. Optimal Robust Control.
Methods for Controller Design Using Genetic
Algorithms. Predictive and Structure Variable Control.
Design Methods and Results. Tuning Fuzzy Logic
Controllers for Robust Control Design. GA-Fuzzy
Hierarchical Control Design Approach. Autonomous Robot
Navigation through Fuzzy-Genetic Programming. Robust
Control Systems Design: A Hybrid
H-Infinity/Multi-Objective Optimization Approach.
Appendices.

About the author

Jamshidi, Mo; Krohling, Renato A.; dos S. Coelho, Leandro; Fleming, Peter J.

Summary

Links genetic algorithms (GAs) and the design of robust control systems. Laying a foundation in the basics of GAs and genetic programming, this work demonstrates the power of these tools for developing optimal robust controllers for linear control systems, optimal disturbance rejection controllers, and predictive and variable structure control.

Product details

• Authors: Leandro Dos S. Coelho, Peter J. Fleming, Mo Jamshidi, Renato A. Krohling, Krohling Renato A.
• Publisher: Taylor and Francis
• Languages: English
• Product format: Hardback
• Released: 14.10.2002
• EAN: 9780849312519
• ISBN: 978-0-8493-1251-9
• No. of pages: 228
• Weight: 590 g
• Illustrations: schwarz-weiss Illustrationen, Tabellen, schwarz-weiss
• Subjects: Guides; Natural sciences, medicine, IT, technology > Technology > Electronics, electrical engineering, communications engineering; TECHNOLOGY & ENGINEERING / Automation, SCIENCE / Life Sciences / Genetics & Genomics, Automatic control engineering, Genetics (non-medical)