Publications

C. W. Scherer. Robust $H_2$-controller design under structured noise uncertainty. 15th IFAC World Congress, 6 pages, Barcelona, 2002. [PUMA: peerReviewed stochastic imng] URL

Matthias Lorenzen, Fabrizio Dabbene, Roberto Tempo, und Frank Allgöwer. Constraint-Tightening and Stability in Stochastic Model Predictive Control. IEEE Trans. Automat. Control, (62)7:3165-3177, 2017. [PUMA: control;chance stability;Numerical processes;Uncertainty;Stochastic control;randomized Asymptotic stability;Optimization;Predictive predictive control horizon constraints;constrained control;discrete-time stochastic control;Robustness;Stochastic model systems;predictive algorithms;receding]

Matthias Lorenzen, Matthias A. Müller, und Frank Allgöwer. Stochastic Model Predictive Control without Terminal Constraints. Int. J. Robust and Nonlinear Control, 2017. [PUMA: without predictive control terminal constraints, constrained systems, nonlinear stochastic control, model MPC]

Florian A. Bayer, Matthias A. Müller, und Frank Allgöwer. On optimal system operation in robust economic MPC. Automatica, (88):98 - 106, 2018. [PUMA: Economic disturbances Robust predictive Stochastic control, model] URL

M. Köppel, I. Kröker, und C. Rohde. Stochastic Modeling for Heterogeneous Two-Phase Flow. In Jürgen Fuhrmann, Mario Ohlberger, und Christian Rohde (Hrsg.), Finite Volumes for Complex Applications VII-Methods and Theoretical Aspects, (77):353-361, Springer International Publishing, 2014. [PUMA: volume in method finite media; stochastic porous Flow vorlaeufig Hybrid Galerkin] URL

Ilja Kr�ker, Wolfgang Nowak, und Christian Rohde. A stochastically and spatially adaptive parallel scheme for uncertain and nonlinear two-phase flow problems. Comput. Geosci., (19)2:269--284, Springer International Publishing, 2015. [PUMA: Finite Nonlinear volume Galerkin; stochastic Stochastic vorlaeufig method; Hybrid] URL

Jan Kelkel, und Christina Surulescu. On a stochastic reaction--diffusion system modeling pattern formation on seashells. Journal of Mathematical Biology, (60)6:765--796, Springer-Verlag, 2010. [PUMA: 60H15, reaction--diffusion 35K57, equations, 92C15 Stochastic formation, vorlaeufig Pattern] URL

Andrea Barth, Raimund Burger, Ilja Kroeker, und Christian Rohde. Computational uncertainty quantification for a clarifier-thickener model with several random perturbations: A hybrid stochastic Galerkin approach. COMPUTERS & CHEMICAL ENGINEERING, (89):11-26, PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND, Juni 2016. [PUMA: Finite Uncertainty Polynomial quantification; chaos; Hybrid method} projection; Galerkin volume Galerkin; stochastic model; {Clarifier-thickener]

Andrea Barth, Santiago Moreno-Bromberg, und Oleg Reichmann. A Non-stationary Model of Dividend Distribution in a Stochastic Interest-Rate Setting. COMPUTATIONAL ECONOMICS, (47)3:447-472, SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS, März 2016. [PUMA: Finite methods control; for Numerical differential method} Singular equations; distribution; stochastic element {Dividend partial]

Florian A. Bayer, Matthias Lorenzen, Matthias A. Mueller, und Frank Allgoewer. Robust economic Model Predictive Control using stochastic information. AUTOMATICA, (74):151-161, PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND, Dezember 2016. [PUMA: disturbances} Robust {Economic control; predictive Stochastic model]