Optimization of PID Controllers Using Ant Colony and Genetic Algorithms: 449 (Studies in Computational Intelligence, 449) - Hardcover

Ünal, Muhammet; Ak, Ayça; Topuz, Vedat; Erdal, Hasan

Hardcover

ISBN 10: 3642328997 ISBN 13: 9783642328992

Publisher: Springer, 2012

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.

About this title

From the Back Cover

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.

Edition details

• Publisher: Springer
• Publication date: 2012
• Language: English
• ISBN 10: 3642328997
• ISBN 13: 9783642328992
• Binding: Hardcover
• Number of pages: 108