Abstract
For chemical processes, dynamic optimization is employed for process transition. On the basis of the multilayer control structure, the employment of dynamic optimization is affected by the regulatory control system. To avoid the adjustment of the regulatory control system, set-point optimization is proposed. For comparison, two types of optimization models, namely direct optimization and set-point optimization, are formulated. The superiority of set-point optimization is rigorously proven. By simulating the commercial process of a throughput-fluctuating ethylene column, the integrated absolute error and maximum deviation of product quality are reduced by more than 150% with set-point optimization. The results indicate that the approach to process transition via regulatory controllers not only avoids the insecurity caused by the switching of set-point controllers but also improves the optimization performance. In conclusion, the proposed optimization structure, namely set-point optimization, is operable and stable for commercial chemical process transitions.