Einladung zum Vortrag im Kolloquium Technische Kybernetik

 Optimizing Process Economic Performance
with Model Predictive Control

Prof. Dr. James B. Rawlings
Department of Chemical and Biological Engineering
University of Wisconsin
Madison, USA

    Zeit: Tuesday, 21. June 2011, 4:00 p.m.
Ort: IST-Seminar-Room 3.243 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen

Abstract

The current paradigm in essentially all industrial advanced process control systems is to decompose a plant's economic optimization into two levels. The first level performs a steady-state optimization. This optimization determines the economically optimal steady-state plant operating conditions (setpoints) and sends these setpoints to the second level, the advanced control system, which performs a dynamic optimization subject to the process constraints. Many advanced process control systems use some form of model predictive control (MPC) for this dynamic optimization
This talk explores the question of how to optimize directly the dynamic process economics, which is known as economic MPC. After defining economic MPC, we show that this control approach does not necessarily lead to stability of the optimal steady-state operating point. Since plant operating goals often include both closed-loop stability as well as economic performance, we show how to modify a purely economic cost function so that steady-state operation is asymptotically stable. We introduce a strong duality assumption and a Lyapunov function based on a rotated stage cost function to estabilsh stability. Next we generalize the approach to stability analysis by introducing a suitable dissipation inequality and storage function.
We also investigate the case when steady operation is not optimal. We develop two modified MPC controllers that guarantee: (i) improved performance compared to optimal periodic control and (ii) satisfaction of constraints on average values of states and inputs.
The talk concludes by presenting open issues for future research including (i) distributed implementation of economic MPC for large-scale systems, and (ii) robustness to disturbances and model errors.

Biographical Information

James B. Rawlings received the B.S. from the University of Texas in 1979 and the Ph.D. from the University of Wisconsin in 1985, both in Chemical Engineering. He spent one year at the University of Stuttgart as a NATO postdoctoral fellow and then joined the faculty at the University of Texas. He moved to the University of Wisconsin in 1995 and is currently the Paul A. Elfers Professor of Chemical and Biological Engineering and the co-director of the Texas-Wisconsin-California Control Consortium (TWCCC).
His research interests are in the areas of chemical process modeling, molecular-scale chemical reaction engineering, monitoring and control, nonlinear model predictive control and moving horizon state estimation.