Data-driven predictive control of oxygen content in flue gas for municipal solid waste incineration process

被引：2
|
作者：
Sun J. [1 ]
Meng X. [2 ]
Qiao J.-F. [3 ]
机构：
[1] Faculty of Information Technology, Beijing University of Technology, Beijing
[2] Beijing Laboratory of Smart Environmental Protection, Beijing
[3] Engineering Research Center of Intelligence Perception and Autonomous Control, Ministry of Education, Beijing
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2024年 / 41卷 / 03期
基金：
中国国家自然科学基金;
关键词：
model predictive control; municipal solid waste incineration; oxygen content in flue gas control; self-organizing long-short term memory network;
D O I：
10.7641/CTA.2023.20622
中图分类号：
学科分类号：
摘要：
The accurate control of oxygen content in flue gas is of great significance to the stable and efficient operation of the municipal solid waste incineration plant. However, it is difficult to achieve effective control performance of oxygen content in flue gas due to the inherent nonlinearity and uncertainty of the municipal solid waste incineration process. Therefore, a data-driven predictive control scheme of oxygen content in flue gas is proposed for municipal solid waste incineration process. Firstly, the prediction model based on the self-organizing long short-term memory (SOLSTM) network is designed. The structure of the hidden layer is dynamically adjusted by integrating the activity and significance of neurons, and then the prediction accuracy of oxygen content in flue gas is improved. Secondly, the gradient descent method is utilized to obtain the control law, and the optimization efficiency is guaranteed. Thirdly, the stability of the proposed control scheme is analyzed based on the Lyapunov theory. Finally, the effectiveness of the proposed control method is verified based on the industrial data. Compared with other methods, the proposed method achieves stable and efficient control performance for oxygen content in flue gas. © 2024 South China University of Technology. All rights reserved.
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页码：484 / 495
页数：11
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