Research of Intelligent Control Policy on Main Steam Temperature of Thermal Power Plant

被引：4

作者：

Luo Yu-feng ^{[1
]}

Liu Lu-lu ^{[1
]}

机构：

[1] Henan Polytech Univ, Coll Elect Engn & Automat, Jiaozuo 454000, Henan, Peoples R China

来源：

ELECTRICAL INFORMATION AND MECHATRONICS AND APPLICATIONS, PTS 1 AND 2 | 2012年 / 143-144卷

关键词：

main steam temperature control; fuzzy control; neuron network; fuzzy neural network; genetic algorithms;

D O I：

10.4028/www.scientific.net/AMM.143-144.307

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In view of the nonlinear, time-variable, long delay, large inertia character of main steam temperature system, the difficult point of control is summarized. The status quo of application study on main steam temperature by fuzzy control, neural network and fuzzy neural network control, genetic algorithms is introduced. And taking "the 600 MW concurrent boiler load in 100%" as an example, carry on the main steam temperature control simulation by means of Matlab/Simulink software. In this simulation, four control strategies are taking for the simulation experiment, and comparing with the traditional PID control algorithm. The simulation results prove that fuzzy neural network control strategies have good robustness, fast response, short setting time, and great potential for the control of main steam temperature.

引用

页码：307 / 311

页数：5

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