Dynamic start-up optimization of a plate reactor with uncertainties

In this paper, start-up of a plate reactor with an exothermic reaction is considered. Dynamic optimization is used to obtain start-up trajectories, while a feedback control system is designed for on-line control. The problem is challenging, since the process model is highly nonlinear, and subject to uncertainty. Limited bandwidth of the feedback control system requires that the optimization gives optimal solutions with low sensitivity to uncertainty. Special attention is given to the problem of formulating an optimal control problem based on physical insight to reduce the sensitivity of the solution, thus increasing the overall robustness of the closed loop system. The resulting solutions are evaluated in Monte Carlo simulations. The study shows that introducing concentration constraints on the injected chemical in combination with high frequency penalties on the control signals lead to less sensitive optimal solutions, thus yielding a more robust start-up. Automatic computer tools that greatly simplifies the task of formulating complex dynamic optimization problems have been used to obtain the start-up trajectories and are briefly presented.