TY  - GEN
TY  - GEN
T1  - Optimization of PID Controllers Using Ant Colony and Genetic Algorithms
T2  - Studies in Computational Intelligence,
A1  - Ünal, Muhammet.
A2  - Ak, Ayça.
A2  - Topuz, Vedat.
A2  - Erdal, Hasan.
LA  - English
PP  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg : Imprint: Springer
YR  - 2013
ED  - 1st ed. 2013.
UL  - http://discoverylib.upm.edu.my/discovery/Record/978-3-642-32900-5
AB  - 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.
OP  - 88
CN  - Q342
SN  - 9783642329005
KW  - Computational intelligence.
KW  - Control engineering.
KW  - Artificial intelligence.
KW  - Computational Intelligence.
KW  - Control and Systems Theory.
KW  - Artificial Intelligence.
ER  -