In this work we propose a scheduling and control formulation for simultaneously addressing scheduling and control problems by explicitly incorporating process dynamics in the form of system constraints that ought to be met. The formulation takes into account the interactions between such problems and is able to cope with nonlinearities embedded into the processing system. The simultaneous scheduling and control problems is cast as a Mixed-Integer Dynamic Optimization (MIDO) problem where the simultaneous approach, based on orthogonal collocation on finite elements, is used to transform it into a Mixed-Integer Nonlinear Programming (MINLP) problem. The proposed simultaneous scheduling and control formulation is tested using three multiproduct continuous stirred tank reactors featuring hard nonlinearities.2

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We consider dynamic optimization strategies for grade transitions for high-impact polystyrene reactors. Because our desired operating conditions are at unstable points, we apply a simultaneous dynamic optimization (SDO) approach, where state and control variables in the optimal control problem are discretized and a large-scale nonlinear programming solver is applied. For this purpose, we consider Radau collocation on finite elements and the IPOPT NLP solver. In addition, we describe the stability of the SDO strategy through the presentation of dichotomy properties for boundary-value problems. The resulting SDO approach is then demonstrated on a wide variety of operating scenarios for the high-impact polystyrene (HIPS) reactor, with highly reliable and efficient performance results.