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...

Full description

Bibliographic Details
Main Authors: <U+00dc>nal, Muhammet. (Author), Ak, Ayȧ. (Author), Topuz, Vedat. (Author), Erdal, Hasan. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Series:Studies in Computational Intelligence, 449
Subjects:
Online Access:https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-32900-5
LEADER 02806nam a22004935i 4500
001 15030
003 DE-He213
005 20130727060153.0
007 cr nn 008mamaa
008 120913s2013 gw | s |||| 0|eng d
020 # # |a 9783642329005  |9 978-3-642-32900-5 
024 7 # |a 10.1007/978-3-642-32900-5  |2 doi 
050 # 4 |a Q342 
072 # 7 |a UYQ  |2 bicssc 
072 # 7 |a COM004000  |2 bisacsh 
082 0 4 |a 006.3  |2 23 
100 1 # |a <U+00dc>nal, Muhammet.  |e author. 
245 1 0 |a Optimization of PID Controllers Using Ant Colony and Genetic Algorithms  |c by Muhammet <U+00dc>nal, Ayȧ Ak, Vedat Topuz, Hasan Erdal.  |h [electronic resource] / 
264 # 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2013. 
300 # # |a XX, 85 p. 65 illus.  |b online resource. 
336 # # |a text  |b txt  |2 rdacontent 
337 # # |a computer  |b c  |2 rdamedia 
338 # # |a online resource  |b cr  |2 rdacarrier 
347 # # |a text file  |b PDF  |2 rda 
490 1 # |a Studies in Computational Intelligence,  |v 449  |x 1860-949X ; 
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 Engineering. 
650 # 0 |a Artificial intelligence. 
650 1 4 |a Engineering. 
650 2 4 |a Computational Intelligence. 
650 2 4 |a Control. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
700 1 # |a Ak, Ayȧ.  |e author. 
700 1 # |a Topuz, Vedat.  |e author. 
700 1 # |a Erdal, Hasan.  |e author. 
710 2 # |a SpringerLink (Online service) 
773 0 # |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783642328992 
830 # 0 |a Studies in Computational Intelligence,  |v 449  |x 1860-949X ; 
856 4 0 |u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-32900-5 
912 # # |a ZDB-2-ENG 
950 # # |a Engineering (Springer-11647)