Hierarchical Optimal Control for Sulfidation Process in Non-Ferrous Metallurgy CPS

Industrial cyber-physical system (ICPS) features the deep integration of the digital model and the industrial physical system, which enables the model-driven techniques to model the state of the industrial physical system. However, the complex reaction mechanism and equipment structure impose challenges to achieving precise decision-making and accurate control in sulfidation process (SfP) in non-ferrous metallurgy CPS. To address this issue, a hierarchical optimal control method is proposed for SfP under the framework of ICPS. Specifically, in order to solve the difficulties of accurately modeling of SfP, a multi-reactor cascade model is established by analyzing the mechanism of reactions and the structure of equipment. In order to realize the optimal control of SfP, an optimization model of SfP is constructed by proposing a quantitative description of copper-arsenic separation innovatively, and the optimal set values of metal ions concentration in cascade reactors are obtained by global optimization in the upper layer of the hierarchical optimal control strategy. After that, the optimal set values are tracked by means of model predictive control in the lower layer. Finally, the proposed method is compared with some state-of-the-art methods, and the key indicators, including copper removal efficiency and arsenic removal efficiency of the proposed method, are superior to the comparative methods.