A Robust and Efficient Mixed-Integer Non-Linear Dynamic Optimization Approach for Simultaneous Design and Control

In this work, we propose a new algorithm for addressing the simultaneous design and control problem through the robust and efficient solution of a Mixed-Integer Dynamic Optimization (MIDO) problem. The algorithm is based on the transformation of the MIDO problem into a Mixed-Integer Nonlinear Programming (MINLP) program through the discretization of the MIDO problem. In this approach both the manipulated and controlled variables are discretized along the expected solution trajectory. This leads to a MINLP problem whose solution provides the full manipulated and controlled time variable profiles and the process design structure aiming to reduce operability problems. The new algorithm for addressing the solution of the MIDO problem has been applied to a system of two series connected continuous stirred tank reactors where a first order reaction takes place. Our results demonstrate that the new approach is able to efficiently address the solution of the simultaneous design and control problem in a systematic way.