TY  - BOOK
AU  - Ünal,Muhammet
AU  - Ak,Ayça
AU  - Topuz,Vedat
AU  - Erdal,Hasan
ED  - SpringerLink (Online service)
TI  - Optimization of PID Controllers Using Ant Colony and Genetic Algorithms
T2  - Studies in Computational Intelligence,
SN  - 9783642329005
AV  - Q342 
U1  - 006.3 23
PY  - 2013///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Engineering
KW  - Artificial intelligence
KW  - Computational intelligence
KW  - Control engineering
KW  - Computational Intelligence
KW  - Control
KW  - Artificial Intelligence (incl. Robotics)
N1  - Artificial Neural Networks -- Genetic Algorithm -- Ant Colony Optimization (ACO) -- An Application for Process System Control
N2  - 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
UR  - http://dx.doi.org/10.1007/978-3-642-32900-5
ER  -