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
Tuesday, 21. June 2011, 4:00 p.m.
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.
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