Optimization of PID Controllers Using Ant Colony and Genetic Algorithms

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 avai...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Ünal, Muhammet (Autor), Ak, Ayça (Autor), Topuz, Vedat (Autor), Erdal, Hasan (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:Studies in Computational Intelligence, 449
Temas:
Computational intelligence.
Control engineering.
Artificial intelligence.
Computational Intelligence.
Control and Systems Theory.
Artificial Intelligence.
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Optimization of PID Controllers Using Ant Colony and Genetic Algorithms  |h [electronic resource] /  |c by Muhammet Ünal, Ayça Ak, Vedat Topuz, Hasan Erdal. 
250 |a 1st ed. 2013. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2013. 
300 |a XX, 88 p.  |b online resource. 
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490 1 |a Studies in Computational Intelligence,  |x 1860-9503 ;  |v 449 
505 0 |a Artificial Neural Networks -- Genetic Algorithm -- Ant Colony Optimization (ACO) -- An Application for Process System Control. 
520 |a 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. 
650 0 |a Computational intelligence. 
650 0 |a Control engineering. 
650 0 |a Artificial intelligence. 
650 1 4 |a Computational Intelligence. 
650 2 4 |a Control and Systems Theory. 
650 2 4 |a Artificial Intelligence. 
700 1 |a Ak, Ayça.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Topuz, Vedat.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Erdal, Hasan.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
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776 0 8 |i Printed edition:  |z 9783642329012 
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830 0 |a Studies in Computational Intelligence,  |x 1860-9503 ;  |v 449 
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950 |a Engineering (R0) (SpringerNature-43712) 

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