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Self-optimizing control: Effective Implementation of optimal operation using Off-Line Computations

The computational effort involved in the solution of real-time dynamic optimization problems (paradigm 1) can be very demanding. Hence, simple but effective implementations of close-to optimal policies are attractive. The main idea is to use off-line calculations and analysis to determine the structure and properties of the optimal solution (paradigm 2). From this the idea is to determine alternate representations of the optimal solution that are more suitable for implementation.
In essence, paradigm 2 includes the use of feedback control with a precomputed controller K. However, standard feedback control assumes that the objective is to control signals (controlled variables) at or close to given values (setpoints). In particular, it does not deal with the very important decision on "what to control" (selection of controlled variables) which up to now has been the focus of "self-optimizing control". The idea is that the controlled variables should be selected such that keeping them constant (or at a precomputed trajectory) by itself gives close-to-optimal operation (without the need for online reoptimization).
Other related issues, not normally dealt with by feedback control, is the selection of optimal switching policies. One approach here is "explicit MPC", but for most realistic problems this can not be used. Thus, the goal to derive simpler policies. The "problem" is to be to find how to do this in a systematic manner.... Some ideas are presented in the talk.

Type of Seminar:
Public Seminar
Prof. Sigurd Skogestad
Head of Department of Chemical Engineering ,NTNU, Trondheim, Norway
Jan 23, 2009   16:15 /

ETH Zentrum, Building ETZ, Room E 6
Contact Person:

Prof. Manfred Morari
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Biographical Sketch:
Sigurd Skogestad received his Ph.D. degree from the California Institute of Technology, Pasadena, USA in 1987. He has been a full professor at Norwegian University of Science and Technology (NTNU), Trondheim, Norway since 1987 and Head of Department of Chemical Engineering since 1999. He is the principal author, together with Prof. Ian Postlethwaite, of the book "Multivariable feedback control" published by Wiley in 1996 (first edition) and 2005 (second edition). He received the Ted Peterson Award from AIChE in 1989, the George S. Axelby Outstanding Paper Award from IEEE in 1990, the O. Hugo Schuck Best Paper Award from the American Automatic Control Council in 1992, and the Best Paper Award 2004 from Computers and Chemical Engineering. He was an Editor of Automatica during the period 1996-2002. His research interests include the use of feedback as a tool to make the system well-behaved (including self-optimizing control), limitations on performance in linear systems, control structure design and plantwide control, interactions between process design and control, and distillation column design, control and dynamics.