Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system

doi:10.1016/j.cjche.2023.11.014

中国化学工程学报 ›› 2024, Vol. 67 ›› Issue (3): 182-194.DOI: 10.1016/j.cjche.2023.11.014

Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system

Shan Liu¹, Wenqi Zhong¹, Li Sun¹, Xi Chen¹, Rafal Madonski²

1 School of Energy and Environment, Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, Southeast University, Nanjing 210096, China;
2 Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwise 44-100, Poland

收稿日期:2023-04-12 修回日期:2023-11-01 出版日期:2024-03-28 发布日期:2024-06-01
通讯作者: Wenqi Zhong,Tel.:+86 25 83794938 Fax:+86 25 83795508 E-mail address:wqzhong@seu.edu.cn.
基金资助:
This work was supported by the key project of the National Nature Science Foundation of China (51736002).

Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system

Shan Liu¹, Wenqi Zhong¹, Li Sun¹, Xi Chen¹, Rafal Madonski²

1 School of Energy and Environment, Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, Southeast University, Nanjing 210096, China;
2 Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwise 44-100, Poland

Received:2023-04-12 Revised:2023-11-01 Online:2024-03-28 Published:2024-06-01
Contact: Wenqi Zhong,Tel.:+86 25 83794938 Fax:+86 25 83795508 E-mail address:wqzhong@seu.edu.cn.
Supported by:
This work was supported by the key project of the National Nature Science Foundation of China (51736002).

摘要/Abstract

摘要： Wet flue gas desulphurization technology is widely used in the industrial process for its capability of efficient pollution removal. The desulphurization control system, however, is subjected to complex reaction mechanisms and severe disturbances, which make for it difficult to achieve certain practically relevant control goals including emission and economic performances as well as system robustness. To address these challenges, a new robust control scheme based on uncertainty and disturbance estimator (UDE) and model predictive control (MPC) is proposed in this paper. The UDE is used to estimate and dynamically compensate acting disturbances, whereas MPC is deployed for optimal feedback regulation of the resultant dynamics. By viewing the system nonlinearities and unknown dynamics as disturbances, the proposed control framework allows to locally treat the considered nonlinear plant as a linear one. The obtained simulation results confirm that the utilization of UDE makes the tracking error negligibly small, even in the presence of unmodeled dynamics. In the conducted comparison study, the introduced control scheme outperforms both the standard MPC and PID (proportional-integral-derivative) control strategies in terms of transient performance and robustness. Furthermore, the results reveal that a lowpass-filter time constant has a significant effect on the robustness and the convergence range of the tracking error.

关键词: Desulphurization system, Disturbance rejection, Model predictive control, Uncertainty and disturbance estimator, Nonlinear system

Abstract: Wet flue gas desulphurization technology is widely used in the industrial process for its capability of efficient pollution removal. The desulphurization control system, however, is subjected to complex reaction mechanisms and severe disturbances, which make for it difficult to achieve certain practically relevant control goals including emission and economic performances as well as system robustness. To address these challenges, a new robust control scheme based on uncertainty and disturbance estimator (UDE) and model predictive control (MPC) is proposed in this paper. The UDE is used to estimate and dynamically compensate acting disturbances, whereas MPC is deployed for optimal feedback regulation of the resultant dynamics. By viewing the system nonlinearities and unknown dynamics as disturbances, the proposed control framework allows to locally treat the considered nonlinear plant as a linear one. The obtained simulation results confirm that the utilization of UDE makes the tracking error negligibly small, even in the presence of unmodeled dynamics. In the conducted comparison study, the introduced control scheme outperforms both the standard MPC and PID (proportional-integral-derivative) control strategies in terms of transient performance and robustness. Furthermore, the results reveal that a lowpass-filter time constant has a significant effect on the robustness and the convergence range of the tracking error.

Key words: Desulphurization system, Disturbance rejection, Model predictive control, Uncertainty and disturbance estimator, Nonlinear system

Shan Liu, Wenqi Zhong, Li Sun, Xi Chen, Rafal Madonski. Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system[J]. 中国化学工程学报, 2024, 67(3): 182-194.

Shan Liu, Wenqi Zhong, Li Sun, Xi Chen, Rafal Madonski. Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system[J]. Chinese Journal of Chemical Engineering, 2024, 67(3): 182-194.

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Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system

Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system

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