A Nonlinear Dynamic Optimization Algorithm for Ethylene Glycol Plant

a nonlinear dynamic optimization algorithm for ethylene glycol plant is proposed in this paper. The nonlinear steady-state model and linear dynamic prediction model based on AI big data method are combined to a nonlinear dynamic optimization model. At the same time, it integrates module functions such as nonlinear gain update and controller collaboration, which not only ensures the consistency of optimization and control models, but also responds to the dynamic characteristics of the process in a timely manner and dynamically optimizes the process in real time. The method proposed effectively ensures the online real-time closed-loop operation of the ethylene glycol plant, as well as achieves the goal of optimizing operation that improving the economic benefits of the plant.