Einladung zum Vortrag im Kolloquium Technische Kybernetik
Measurement-based Optimization via Tracking of Necessary Conditions
Prof. Dominique Bonvin, Ph.D.
Zeit: Dienstag · 26. 11. 2002 · 16:00 Uhr
Ort: Hörsaal V 9. 31 · Pfaffenwaldring 9 · Campus Stuttgart-Vaihingen
Abstract
The optimization of production processes has attracted more attention in recent years since, in the face of growing competition, it is a natural choice for reducing production costs, improving product quality, and meeting safety requirements or environmental regulations. Since the models available in industry carry a large amount of uncertainty, the standard model-based optimization techniques are often ineffective. Thus, optimization methods that use measurements to overcome the effect of uncertainty are of considerable interest.
In this talk, a novel measurement-based optimization framework is presented, where optimality is achieved by tracking the necessary conditions of optimality. For ease of implementation, these conditions are partitioned into constraint-seeking and sensitivityseeking elements. The constraint-seeking elements of the inputs are used to meet the corresponding constraints. Since the same framework applies to both continuous and batch processes, it will be illustrated in simulation for the optimization of a continuous and a discontinuous reactor in the presence of uncertainty.
Biografische Information
Dominique Bonvin is Professor of Automatic Control at the Swiss Federal Institute of Technology (EPFL) in Lausanne, Switzerland. He received his Diploma in Chemical Engineering from the ETH, Zurich, and his Ph.D. degree from the University of California, Santa Barbara. He worked in the field of process control for the Sandoz Corporation in Basel and with the Systems Engineering Group of the ETH Zurich. He joined the EPFL in 1989 where his current research interests include modeling, identification and optimization of dynamical systems. He serves as Associate Editor for the journals Control Engineering Practice and Journal of Process Control.
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