Research on Water Level Optimal Control of Boiler Drum Based on Dual Heuristic Dynamic Programming

被引：0

作者：

Huang, Qingbao ^{[1
]}

Song, Shaojian ^{[1
]}

Lin, Xiaofeng ^{[1
]}

Peng, Kui ^{[1
]}

机构：

[1] Guangxi Univ, Coll Elect Engn, Nanning 530004, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2011, PT I | 2011年 / 6675卷

关键词：

boiler drum level; BP neural network; dual heuristic dynamic programming; optimal control;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Boiler drum system is an important component of a thermal power plant or industrial production, and the water level is a critical parameter of boiler drum control system. Because of non-linear, strong coupling and large disturbance, it is difficult to reach a suitable working state of drum system by using traditional control methods. It is necessary to explore new methods to realize optimal control of drum water level. The back propagation (BP) neural network model of boiler drum system is built in this paper firstly, then the optimal control of the drum system by the dual heuristic dynamic programming (DHP) algorithm is realized, and compared with the heuristic dynamic programming (HDP) algorithm at last. The result shows that the DHP optimization algorithm has good performance in control precision and rejecting process disturbances.

引用

页码：455 / 463

页数：9

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