Main Steam Temperature PID Controller of Power Plant Based on Genetic Algorithm and Neural Networks

被引：0

作者：

Zhao Jing ^{[1
]}

Fu Jun-fang ^{[1
]}

Chen Hong-wen ^{[2
]}

Zhang Liang ^{[3
]}

Li Meng-jie ^{[3
]}

机构：

[1] Henan Elect Power Survey & Design Inst, Zhengzhou, Peoples R China

[2] Inner Mongonia Daihai Elect Power Generat Co Ltd, Liangcheng, Peoples R China

[3] Datang Int Panshan Power Generat Co Ltd, Tianjin, Peoples R China

来源：

2011 INTERNATIONAL CONFERENCE ON FUTURE COMPUTER SCIENCE AND APPLICATION (FCSA 2011), VOL 3 | 2011年

关键词：

genetic algorithm; BP neural networks; PID control; MATLAB simulation;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A Modified genetic algorithm was introduced. And the PID controller, based on the back-propagation neural networks optimized by the genetic algorithm, was presented in order to overcome the shortcoming of conventional PID controller without self-optimization. The on-line adjustment of its three parameters was realized. Taking the main steam temperature of power plant as the research object, the MATLAB simulation was carried out. The results showed that it had better self-study and self-adaptive ability.

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页码：463 / 466

页数：4