Integrated scheduling and control of a polymerization reactor with online closed-loop implementation

Scheduling and control problems are traditionally solved sequentially. However, integration of both problems can result in a better overall performance. A main challenge in the integration is the solution to the derived mixed-integer dynamic optimization (MIDO) problem. To overcome the challenge, we present a novel integration method, which simultaneously determines the PI controller design and the scheduling decisions. The method decomposes the MIDO problem. The dynamic optimization for each transition can be solved independently offline. A set of controller candidates are generated and stored. Then the integrated problem is transformed into a mixed-integer nonlinear fractional programming problem of scheduling with controller selection. This problem can be efficiently solved to the global optimaity by the Dinkelbach's algorithm.