Title :
Tuning PID controller using adaptive genetic algorithms
Author :
Lin, Guohan ; Liu, Guofan
Author_Institution :
Dept. of Electr. & Inf., Hunan Inst. of Eng., Xiangtan, China
Abstract :
Proportional Integral Derivative (PID) controllers are widely used as a means of controlling system outputs. Many techniques have been developed to tune the PID parameters. In this article, adaptive genetic algorithms (AGA) are proposed as a method for PID optimization and compared with those of traditional optimizations methods. Simulations with different processes show that the gains obtained using adaptive genetic algorithms (AGA) provide better performance than those obtained by the classical Ziegler-Nichols (ZN) method and classical genetic algorithms (CGA) method.
Keywords :
control system synthesis; genetic algorithms; three-term control; PID optimization; Ziegler-Nichols method; adaptive genetic algorithms; classical genetic algorithms method; proportional integral derivative controllers; tuning PID controller; Biological cells; Control systems; Gallium; Genetic algorithms; Optimization; Tuning; Zinc; Auto Tuning; Genetic algorithms; PID controller; Ziegler Nichols Method;
Conference_Titel :
Computer Science and Education (ICCSE), 2010 5th International Conference on
Conference_Location :
Hefei
Print_ISBN :
978-1-4244-6002-1
DOI :
10.1109/ICCSE.2010.5593559