NDLI: Thermal Process System Identification Using Particle Swarm Optimization

Content Provider	IEEE Xplore Digital Library
Author	Ze Dong Pu Han Dongfeng Wang Songming Jiao
Copyright Year	2006
Description	Author affiliation: Dept. of Autom., North China Electr. Power Univ. (Ze Dong; Pu Han; Dongfeng Wang; Songming Jiao)
Abstract	System identification adopting an open loop step response curve is a feasible way to obtain the mathematic model of the control object. Due to the satisfying performance in global optimization, evolution computing (EC) methods such as genetic algorithm have been applied to the open loop step response curve analysis and achieved effective results. In this paper, particle swarm optimization (PSO) algorithm which is considered as a new relative addition to the EC methods is introduced to solve the system identification problem for thermal process control objects. Typical forms of transfer functions for the thermal process are adopted, utilizing PSO algorithm to estimate the parameters, for the convenient application of which, a set of software is also developed. With these softwares, some characters of the experimental data are specified by the user. And then the initial values for the model parameters are deduced from these characters. Around these initial values, a smaller search space is determined, within which the PSO algorithm searches the optima for the model parameters. Thus the search efficiency can be improved remarkably. The software has been applied in some power plants, the results of which prove the effectiveness of the method
Starting Page	194
Ending Page	198
File Size	5378321
Page Count	5
File Format	PDF
ISBN	1424404967
DOI	10.1109/ISIE.2006.295591
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-09
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	System identification Particle swarm optimization Mathematics Mathematical model Open loop systems Optimization methods Genetic algorithms Performance analysis Algorithm design and analysis Process control
Content Type	Text
Resource Type	Article

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