Optimization of PID Controllers Using Ant Colony and Genetic Algorithms

✍ Scribed by Muhammet Ünal, Ayça Ak, Vedat Topuz, Hasan Erdal (auth.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2013
• Tongue: English
• Leaves: 95
• Series: Studies in Computational Intelligence 449
• Edition: 1
• Category: Library

✦ Synopsis

Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased, applications of these algorithms have grown in more than equal measure. While many of the books available on these subjects only provide a cursory discussion of theory, the present book gives special emphasis to the theoretical background that is behind these algorithms and their applications. Moreover, this book introduces a novel real time control algorithm, that uses genetic algorithm and ant colony optimization algorithms for optimizing PID controller parameters. In general, the present book represents a solid survey on artificial neural networks, genetic algorithms and the ant colony optimization algorithm and introduces novel practical elements related to the application of these methods to process system control.

✦ Table of Contents

Front Matter....Pages 1-14
Introduction....Pages 1-3
Artificial Neural Networks....Pages 5-17
Genetic Algorithm....Pages 19-29
Ant Colony Optimization (ACO)....Pages 31-35
An Application for Process System Control....Pages 37-68
Conclusion....Pages 69-72
Back Matter....Pages 0--1

✦ Subjects

Computational Intelligence; Control; Artificial Intelligence (incl. Robotics)