Adaptive sliding mode control of petrochemical flare combustion process based on radial basis function network
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Adaptive sliding mode control of petrochemical flare combustion process based on radial basis function network
Adaptive sliding mode control of petrochemical flare combustion process based on radial basis function network
中国化学工程学报(英文版)2024年76卷第12期 页码:318-326
Affiliations:
1. Faculty of Information Technology, Beijing University of Technology,Beijing,China,100124
2. Beijing Laboratory of Smart Environmental Protection,Beijing,China,100124
3. Engineering Research Center of Intelligent Perception and Autonomous Control, Ministry of Education,Beijing,China,100124
4. Baotou Reclaimed Water Resources and Sewage Treatment Co., Ltd.,Inner Mongolia,China,014000
5. Baotou Water Group,Inner Mongolia,China,014000
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纸质出版:2024
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Jiahui Liu, Nan Guo, Yixin Peng, 等. Adaptive sliding mode control of petrochemical flare combustion process based on radial basis function network[J]. 中国化学工程学报(英文版), 2024,76(12):318-326.
Jiahui Liu, Nan Guo, Yixin Peng, Wenlu Li, Junfei Qiao, Xiaolong Gao, Wei Xiong. Adaptive sliding mode control of petrochemical flare combustion process based on radial basis function network[J]. Chinese Journal of Chemical Engineering, 2024, 76(12): 318-326.
Jiahui Liu, Nan Guo, Yixin Peng, 等. Adaptive sliding mode control of petrochemical flare combustion process based on radial basis function network[J]. 中国化学工程学报(英文版), 2024,76(12):318-326.DOI:
Jiahui Liu, Nan Guo, Yixin Peng, Wenlu Li, Junfei Qiao, Xiaolong Gao, Wei Xiong. Adaptive sliding mode control of petrochemical flare combustion process based on radial basis function network[J]. Chinese Journal of Chemical Engineering, 2024, 76(12): 318-326.DOI:
Adaptive sliding mode control of petrochemical flare combustion process based on radial basis function network
Steam-assisted combustion elevated flares are currently the most widely used type of petrochemical flares. Due to the complex and variable composition of the waste gas they handle
the combustion environment is severely affected by meteorological conditions. Key process parameters such as intake composition
flow rate
and real-time data of post-combustion residues are difficult to measure or exhibit lag in data availability. As a result
the control methods for these flares are limited
leading to poor control effectiveness. To address this issue
this paper proposes an adaptive sliding mode control method based on the radial basis function (RBF) network. Firstly
the operational characteristics of the petrochemical flare combustion process are analyzed
and a control model for the combustion process is established based on carbon dioxide detection. Secondly
an RBF neural network-based unknown function approximator is designed to identify the nonlinear part of the actual operating system. Finally
by combining the control model of the petrochemical flare combustion and designing the RBF sliding mode controller with its adaptive control law
fast and stable control of the flare combustion state is achieved. Simulation results demonstrate that the designed control strategy can achieve tracking control of the petrochemical flare combustion state
and the adaptive law also accomplishes system identification.
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