PID controller parameters optimization for the main steam temperature system based on immune algorithm-particle swarm optimization

Author

Gui-li Yuan ; Lei Zhu

Author_Institution

Sch. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China

fYear

2012

fDate

6-8 July 2012

Firstpage

2618

Lastpage

2623

Abstract

In this paper, PID control model was set up for the main steam temperature control system of modern large-scale power plant, combined the immune algorithm and particle swarm optimization, and improved by adding adaptive crossover and adaptive mutation. It is optimized the main steam temperature control system which in typical load conditions with the improved algorithm. By comparison with the traditional genetic algorithm shows, this algorithm has certain advantages on convergence and robustness.

Keywords

adaptive control; genetic algorithms; power generation control; steam power stations; temperature control; three-term control; PID control model; PID controller parameters optimization; adaptive crossover; adaptive mutation; convergence; genetic algorithm; immune algorithm; main steam temperature control system; main steam temperature system; modern large-scale power plant; particle swarm optimization; robustness; typical load conditions; Adaptive systems; Computers; Educational institutions; Intelligent control; Particle swarm optimization; Power systems; Temperature control; PID controller; immune algorithm; main steam temperature control system; particle swarm optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2012 10th World Congress on

Conference_Location

Beijing

Print_ISBN

978-1-4673-1397-1

Type

conf

DOI

10.1109/WCICA.2012.6358315

Filename

6358315