Integration of Production Scheduling and Model Predictive Control under Process Uncertainties
نویسندگان
چکیده
In order to achieve optimal operational conditions, the integration of decision-making across different layers of a company and the consideration of uncertain parameters in view of dynamic market conditions are essential. In this study, we propose a framework for the integration of scheduling and control for nonlinear systems under process uncertainties. The framework includes the use of piecewise affine functions (PWA) to handle non-linearities, a robust model predictive control scheme and the use of surrogate models to derive the closed-loop input-output behavior of the dynamic system. We take a preventive approach in handling disturbances at control level. Through a case study, we evaluate the performance of the framework and evaluate the impacts of such disturbances in scheduling solutions.
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