Research on the Algorithm of Flue Gas Desulfurization System

被引：0
作者：
Hao, HongBo [1 ]
机构：
[1] Tianjin Univ Sci & Technol, Tianjin, Peoples R China
来源：
PROCEEDINGS OF THE 2021 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS (ICAROB 2021) | 2021年
关键词：
flue gas; desulfurization; PID; RBF neural network; Matlab;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the process of flue gas desulfurization and denitrification, which is a nonlinear, time-varying, large lag and strong coupling complex variable process, is analyzed and studied in depth. Based on the analysis of the coupling characteristics of the adsorption tower, the control model of the desulfurization and denitrification process of the adsorption tower is established, and the system identification adaptive PID Decoupling control algorithm is adopted. The Simulink toolbox corresponding to Matlab software is used to simulate and verify the effectiveness of the algorithm. The RBF neural network identifier is used to identify the plant model on-line to improve the adaptive ability of the controller.
引用
收藏
页码：680 / 683
页数：4
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