The PID prediction control system using particle swarm optimization and genetic algorithms

Author

Li, Guo-Dong ; Wang, Chen-Hong ; Masuda, Shiro ; Yamaguchi, Daisuke ; Nagai, Masatake

Author_Institution

Dept. of Syst. Design, Tokyo Metropolitan Univ., Hino, Japan

fYear

2009

fDate

10-12 Nov. 2009

Firstpage

687

Lastpage

691

Abstract

In this paper, the particle swarm optimization (PSO) algorithm and genetic algorithm (GA) are employed to optimize the parameters of PID algorithm in order to improve the performance of PID control system. Moreover, we propose the grey model based on grey system theory to combine with PID control to establish the PID prediction control system. The proposed control system can realize the accurate control in realtime. Finally, we validated the effectiveness of the proposed control system by computer simulation.

Keywords

genetic algorithms; grey systems; particle swarm optimisation; predictive control; three-term control; PID prediction control; genetic algorithm; grey model; grey system theory; particle swarm optimization; Cities and towns; Computer simulation; Control system synthesis; Control systems; Genetic algorithms; Industrial control; Iterative algorithms; Particle swarm optimization; Predictive models; Three-term control;

fLanguage

English

Publisher

ieee

Conference_Titel

Grey Systems and Intelligent Services, 2009. GSIS 2009. IEEE International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-4914-9

Electronic_ISBN

978-1-4244-4916-3

Type

conf

DOI

10.1109/GSIS.2009.5408225

Filename

5408225