Stable Operation Strategy for Near-Zero Discharge Evaporation and Crystallization System of Coal Chemical Wastewater Based on Model Predictive Control (MPC)
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Abstract
With the increasing integration of intelligent sensing, industrial communication networks, and Electromagnetic Waves, Antennas and Propagation technologies in smart process industries, stable control of complex multivariable systems has become essential for reliable information acquisition and distributed decision-making. This study proposes a stable operation strategy for a near-zero discharge evaporation and crystallization system for coal chemical wastewater based on model predictive control (MPC). A discrete state-space model incorporating influent chemical oxygen demand, salt concentration disturbances, liquid level–concentration coupling, and steam network constraints is established to characterize the dynamic behavior of the process. A rolling optimization controller integrating feedforward compensation and quadratic programming is developed to coordinate feed flow, steam regulation, and circulation control under multiple operational constraints. Simulation and industrial validation demonstrate that the proposed strategy reduces liquid level overshoot by 82.4%, decreases steam consumption fluctuation by 66.1%, and maintains stable operation with a water reuse rate above 92.3% under severe disturbance conditions. The results confirm that the MPC-based framework significantly enhances disturbance rejection, robustness, and energy efficiency while providing an effective engineering solution for cyber–physical industrial systems. Furthermore, the proposed architecture offers valuable references for communication-enabled intelligent monitoring, distributed sensing, and industrial automation applications associated with Electromagnetic Waves, Antennas and Propagation technologies.
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