DocumentCode :
3551236
Title :
Modeling identification of power plant thermal process based on PSO algorithm
Author :
Liu, Yijian ; He, Xiongxiong
Author_Institution :
Coll. of Electr. & Autom. Eng., Nanjing Normal Univ., China
fYear :
2005
fDate :
8-10 June 2005
Firstpage :
4484
Abstract :
In order to overcome the disadvantages of common model identification methods for thermal process, a novel identification solution based on the particle swarm optimization (PSO) was proposed in this paper. The effectiveness of the proposed identification algorithm is tested by simulation experiments in the common thermal process models. The experiments show excellent results in term of identification accuracy and effectiveness. The PSO approach provides the characteristics of ease realization and high identification accuracy compared with the identification results by improved genetic algorithm.
Keywords :
artificial intelligence; genetic algorithms; heat systems; identification; power plants; PSO algorithm; genetic algorithm; model identification; particle swarm optimization; power plant thermal process; Control system synthesis; Educational institutions; Fuzzy neural networks; Genetic algorithms; Parameter estimation; Particle swarm optimization; Power generation; Power system modeling; Signal processing; Transfer functions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2005. Proceedings of the 2005
ISSN :
0743-1619
Print_ISBN :
0-7803-9098-9
Electronic_ISBN :
0743-1619
Type :
conf
DOI :
10.1109/ACC.2005.1470703
Filename :
1470703
Link To Document :
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