Stochastic Process Control
Industrial production processes are often operated such that energy consumption or operation costs are minimized. Typically this means full exploitation of the technical facilities so that the process will operate just within the safety limits. Even small disturbances can cause great damage or even danger in this situation, so they have to be corrected immediately. Special optimizing controllers are available for that purpose (Model Predictive Control).
Goal of the project was the investigation of a new approach that takes into account the possible future disturbances in calculating the current correction. This ensures safety but prohibits overly pessimistic corrections that might neutralize the expected savings.
Publications
2004
2001
2000
2004 |
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Marc Steinbach | Robust Process Control by Dynamic Stochastic Programming | ZIB-Report 04-20 (Appeared in : Proc. Appl. Math. Mech. (4)1, (2004) 11-14) |
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2001 |
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Izaskun Garrido, Marc Steinbach | A Multistage Stochastic Programming Approach in Real-Time Process Control | ZIB-Report 01-05 (Appeared in: Online Optimization of Large Scale Systems. M. Grötschel, S. O. Krumke, J. Rambau (eds.) Springer, 2001, pp. 479-498) |
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Marc Steinbach | General Information Constraints in Stochastic Programs | ZIB-Report 01-24 |
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Rene Henrion, Pu Li, Andris Möller, Marc Steinbach, Moritz Wendt, Günter Wozny | Stochastic Optimization for Operating Chemical Processes Under Uncertainty | ZIB-Report 01-04 (Appeared in: Online Optimization of Large Scale Systems, M. Grötschel, S. O. Krumke, J. Rambau (eds.) Springer, 2001, pp. 457-478) |
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Marc Steinbach | Tree-Sparse Convex Programs | ZIB-Report 01-08 (Appeared in: Mathematical Methods of Operations Research 56 (2002) 347-376) |
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2000 |
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Marc Steinbach | Hierarchical Sparsity in Multistage Convex Stochastic Programs | ZIB-Report 00-15 (Appeared in: Stochastic Optimization. Algorithms and Applications, S. P. Uryasev, P. M. Pardalos, Applied Optimization, Vol. 54, Kluwer Academic Publishers, 2001, pp. 385-410) |
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