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Optimization of PID Controllers Using Ant Colony and Genetic Algorithms

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Optimization of PID Controllers Using Ant Colony and Genetic Algorithms 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 Edition

ISBN: 9783642434778
Publication date: 15th October 2014
Author: Muhammet Ünal, Ayça Ak, Vedat Topuz, Hasan Erdal
Publisher: Springer an imprint of Springer Berlin Heidelberg
Format: Paperback
Pagination: 88 pages
Series: Studies in Computational Intelligence
Genres: Artificial intelligence
Automatic control engineering