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

Shan Liu; Wenqi Zhong; Li Sun; Xi Chen; Rafal Madonski

doi:10.1016/j.cjche.2023.11.014

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

Updated：2026-01-06

- 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
- 中国化学工程学报（英文版） 2024年67卷第3期页码：182-194
- Affiliations：
  
  1. School of Energy and Environment, Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, Southeast University,Nanjing,China,210096
  2. Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwise,Poland,44-100
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2023.11.014
  中图分类号：
- 纸质出版：2024
- Accepted：
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Shan Liu, Wenqi Zhong, Li Sun, 等. Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system[J]. 中国化学工程学报（英文版）, 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.
Shan Liu, Wenqi Zhong, Li Sun, 等. Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system[J]. 中国化学工程学报（英文版）, 2024,67(3):182-194. DOI： 10.1016/j.cjche.2023.11.014.

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. DOI： 10.1016/j.cjche.2023.11.014.

摘要

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.

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