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

Chinese Journal of Chemical Engineering 2024年第3期67卷 182-194页

作者： Shan Liu Wenqi Zhong Li Sun Xi Chen Rafal Madonski School of Energy and Environment Key Laboratory of Energy Thermal Conversion and Control of Ministry of EducationSoutheast UniversityNanjing 210096China Faculty of Automatic Control Electronics and Computer ScienceSilesian University of TechnologyGliwise 44-100Poland

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

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Multiobjective economic model predictive control using utopia-tracking for the wet flue gas desulphurization system

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Chinese Journal of Chemical Engineering 2023年第2期54卷 343-352页

作者： Shan Liu Wenqi Zhong Xi Chen Li Sun Lukuan Yang Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing 210096China

Efficient control of the desulphurization system is challenging in maximizing the economic objective while reducing the SO_(2) emission concentration. The conventional optimization method is generally based on a hierarchical structure in which the upper optimization layer calculates the steady-state results and the lower control layer is responsible to drive the process to the target point. However, the conventional hierarchical structure does not take the economic performance of the dynamic tracking process into account. To this end, multi-objective economic model predictive control(MOEMPC) is introduced in this paper, which unifies the optimization and control layers in a single stage. The objective functions are formulated in terms of a dynamic horizon and to balance the stability and economic performance. In the MOEMPC scheme, economic performance and SO_(2) emission performance are guaranteed by tracking a set of utopia points during dynamic transitions. The terminal penalty function and stabilizing constraint conditions are designed to ensure the stability of the system. Finally, an optimized control method for the stable operation of the complex desulfurization system has been established. Simulation results demonstrate that MOEMPC is superior over another control strategy in terms of economic performance and emission reduction, especially when the desulphurization system suffers from frequent flue gas disturbances.

关键词： desulphurization system Economics Economic model predictive control Flue gas Optimization Utopia point

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