Simultaneous mixed-integer dynamic optimization for integrated design and control

We consider strategies for integrated design and control 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) rogram. In this approach, both the manipulated and controlled variables are discretized using a simultaneous dynamic optimization approach. e also develop three MINLP formulations based on a nonconvex formulation, the conventional Big-M formulation and generalized disjunctive rogramming (GDP). In addition, we compare the outer approximation and NLP branch and bound algorithms on these formulations. This problem s applied to a system of two series connected continuous stirred tank reactors where a first-order reaction takes place. Our results demonstrate that he simultaneous MIDO approach is able to efficiently address the solution of the integrated design and control problem in a systematic way. 2006 Elsevier Ltd. All rights reserved.