Robust Control Systems with Genetic Algorithms

Citation

(2003), "Robust Control Systems with Genetic Algorithms", Sensor Review, Vol. 23 No. 3. https://doi.org/10.1108/sr.2003.08723cae.003

Robust Control Systems with Genetic Algorithms

Robust Control Systems with Genetic Algorithms

M. Jamshidi, L dS Coelho, R.A. Krohling and P.J. FlemingCRC Press2003210 pp.ISBN 0-8493-1251-5£38.99

Keywords: Control systems, Genetic algorithms

"Robust Control Systems with Genetic Algorithms" presents design methods for robust controllers using new tools based on genetic algorithms, genetic programming and hybrid approaches incorporating fuzzy logic.

The book comprises nine chapters, with the first addressing Genetic Algorithms. It discusses topics including terms and definitions, fitness functions, genetic operators, genetic algorithms for optimisation, and genetic programming. An introduction to control theory, robust stability and disturbance rejection, controller design and optimisation, are amongst the topics addressed in chapter 2, Optimal Robust Control.

Chapter 3 presents two methods for controller design using genetic algorithms, while chapter 4, Predictive and Variable Structure Control Designs, discusses model-based predictive controllers and variable structure control systems. Optimisation of generalized predictive control design by genetic algorithms, and optimisation of quasi-sliding mode control design by genetic algorithms, is clearly explained in chapter 5.

Tuning Fuzzy Logic Controllers for Robust Control System Design, and GA-Fuzzy Hierarchical Control Design Approach are presented in chapters 6 and 7, respectively. Topics covered in these sections include genetic tuning of fuzzy control systems, fuzzy control system design – for example, study applications of Gas for fuzzy control, and genetic algorithms in knowledge enhancement.

Hierarchical fuzzy-behaviour control, genetic programming of fuzzy behaviours, and autonomous navigation results are amongst the topics discussed in chapter 8, Autonomous Robot Navigation Through Fuzzy-Genetic Programming. The final chapter of the book addresses Robust Control System Design: A Hybrid H-Infinity/ Multiobjective Optimisation Approach. Topics discussed include H-infinity design of robust control systems, multiobjective optimisation, and a case study – robust control of a gasification plant. An appendix covers the fundamental concepts of fuzzy sets, fuzzy logic and fuzzy control.

This book is predominantly aimed at those involved in control engineering, but its well written introduction to genetic algorithms, genetic programming and fuzzy logic makes it suitable for those in other disciplines as well. One of the most important aspects of the book is the variety of applications described.