Optimization of industrial boiler combustion control system based on genetic algorithm

被引：8
|
作者：
Pan, Hongguang [1 ]
Zhong, Weimin [2 ]
Wang, Zaiying [1 ]
Wang, Guoxin [1 ]
机构：
[1] Xian Univ Sci & Technol, Coll Elect & Control Engn, Xian 710054, Shaanxi, Peoples R China
[2] East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China
来源：
COMPUTERS & ELECTRICAL ENGINEERING | 2018年 / 70卷
基金：
中国博士后科学基金; 美国国家科学基金会;
关键词：
Furnace combustion control system; Excess air coefficient; Varying offset dual-crisscross; Genetic algorithm;
D O I：
10.1016/j.compeleceng.2018.03.003
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In the combustion process, the traditional furnace combustion control method cannot meet the control requirements with frequent variable loads. Firstly, for the combustion control system with the varying variable bias and bi-double crossing limit, the ranges of bias coefficients are analyzed gradually. Secondly, the objective function is designed based on the excess air coefficient and the main steam pressure deviation signal. Finally, the genetic algorithm is adopted to optimize the bias coefficients to achieve better control performance. The simulation results show that the presented method can effectively improve the response speed and keep the excess air coefficient in the optimal combustion interval. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码：987 / 997
页数：11
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