Institut für Mathematik > Arbeitsgruppen > Kontinuierliche Optimierung > Team > Prof. Dr. Andreas Potschka

Prof. Dr. Andreas Potschka

Prof. Dr. Andreas Potschka

Institut für Mathematik
Arbeitsgruppe Kontinuierliche Optimierung
Raum 307 / Erzstraße 1
38678 Clausthal-Zellerfeld

Telefon: +49 5323 72-2954
E-Mail: andreas.potschka@tu-clausthal.de

Forschung

Die Arbeitsgruppe Kontinuierliche Optimierung entwickelt und analysiert mathematische Methoden und Algorithmen für hochdimensionale nichtlineare Optimierungsprobleme.

Kurzvita

Andreas schloss sein Diplom (2006), seine Promotion (2011) und seine Habilitation (2018) in Mathematik an der Universität Heidelberg ab. Einen Großteil von 2005 verbrachte er als Complimentary Visiting Scholar an der Rice University in Houston, TX, USA. Von 2012-2020 leitete er die Nachwuchsforschungsgruppe Model-based Optimizing Control am Interdisziplinären Zentrum für Wissenschaftliches Rechnen, Universität Heidelberg. Er ist Träger des Klaus Tschira Preises für verständliche Wissenschaft in Mathematik (2012). Andreas vertrat die Professuren für Optimierung (2014/2015) an der Universität Mannheim und für Numerische Mathematik (2017) an der Universität Heidelberg. Von Februar bis September 2020 arbeitete er als Wissenschaftler am ABB Forschungszentrum Deutschland in Ladenburg. Seit Oktober 2020 ist er Professor für Kontinuierliche Optimierung am Institut für Mathematik der Technischen Universität Clausthal.

Publikationen

Preprints & submitted papers

  • H.G. Bock, D.H. Cebulla, C. Kirches, A. Potschka, Mixed-Integer Optimal Control for Multimodal Chromatography, Computers and Chemical Engineering, submitted
  • C. Leidereiter, D. Kouzoupis, M. Diehl, A. Potschka, Fast optimal pruning for Markov chain scenario tree NMPC, Automatica, to be submitted
  • S. Göttlich, F.M. Hante, A. Potschka, L. Schewe, Penalty alternating direction methods for mixed-integer optimal control with combinatorial constraints, Mathematical Programming Series B, arXiv:1905.13554, submitted
  • S. Sager, F. Bernhardt, F. Kehrle, M. Merkert, A. Potschka, B. Meder, H. Katus, E. Scholz, Expert-enhanced Machine Learning for Cardiac Arrhythmia Classification, Artificial Intelligence in Medicine, submitted

Journal papers (with peer review)

  • H.G. Bock, J. Gutekunst, A. Potschka, M.E. Suaréz Garcéz, A Flow Perspective on Nonlinear Least-Squares Problems, Vietnam Journal of Mathematics, 48(4):987–1003, 2020
  • J. Gutekunst, H.G. Bock, A. Potschka, Economic NMPC for averaged infinite horizon problems with periodic approximations, Automatica. A Journal of IFAC, the International Federation of Automatic Control, 117:109001,13, 2020
  • A. Potschka, H.G. Bock, A Sequential Homotopy Method for Mathematical Programming Problems, Mathematical Programming Series A, doi:10.1007/s10107-020-01488-z, arXiv:19.02.06984, 2020
  • A. Potschka, Backward step control for Hilbert space problems, Numerical Algorithms, 81(1):151–180, 2019
  • S. Göttlich, A. Potschka, C. Teuber, A partial outer convexification approach to control transmission lines, Computational Optimization and Applications, 72(2):431–456, 2019
  • H.G. Bock, C. Kirches, A. Meyer, A. Potschka, Numerical solution of optimal control problems with implicit switches, Optimization Methods and Software, 33(3):450– 474, 2018
  • F. Lenders, C. Kirches, A. Potschka, trlib: A vector-free implementation of the GLTR method for iterative solution of the trust region problem, Optimization Methods and Software, 33(3):420–449, 2018
  • H.C. La, A. Potschka, J.P. Schlöder, H.G. Bock, Dual control and online optimal experimental design, SIAM Journal on Scientific Computing, 39(4):B640–B657, 2017
  • S. Göttlich, A. Potschka, U. Ziegler, Partial Outer Convexification for traffic light optimization in road networks, SIAM Journal on Scientific Computing, 39(1):B53–B75, 2017, featured as SIAM News Research Nugget Mathematically Optimizing Traffic Lights in Road Intersections
  • H.C. La, A. Potschka, H.G. Bock, Partial Stability for Nonlinear Model Predictive Control, Automatica, 78:14–19, 2017
  • A. Potschka, Backward Step Control for globalized Newton-type methods, SIAM Journal on Numerical Analysis, 54(1):361–387, 2016
  • F.M. Hante, M.S. Mommer, A. Potschka, Newton–Picard preconditioners for time-periodic, parabolic optimal control problems, SIAM Journal on Numerical Analysis, 53(5): 2206–2225, 2015
  • H.J. Ferreau, C. Kirches, A. Potschka, H.G. Bock, M. Diehl, qpOASES: A parametric active-set algorithm for quadratic programming, Mathematical Programming Computation, 6(4):327–363, 2014
  • A. Schmidt, A. Potschka, S. Körkel, and H.G. Bock, Derivative-Extended POD Reduced-Order Modeling for Parameter Estimation, SIAM Journal on Scientific Computing, 35(6):A2696–A2717, 2013
  • C. Kirches, A. Potschka, H.G. Bock, S. Sager, A parametric active set method for a subclass of quadratic programs with vanishing constraints, Pacific Journal of Optimization, 9(2):275–299, 2013
  • A. Potschka, M.S. Mommer, J.P. Schlöder, and H.G. Bock, Newton–Picard based preconditioning for linear-quadratic optimization problems with time-periodic parabolic PDE constraints, SIAM Journal on Scientific Computing, 34(2):A1214–A1239, 2012
  • A. Potschka, F. Logist, J.F. Van Impe, H.G. Bock, Tracing the Pareto frontier in bi-objective optimization problems by ODE techniques, Numerical Algorithms, 57(2):217– 233, 2010
  • A. Potschka, H.G. Bock, and J.P. Schlöder, A minima tracking variant of semi-infinite programming for the treatment of path constraints within direct solution of optimal control problems, Optimization Methods and Software, 24:237–252, 2009

Book chapters (with peer review)

  • A. Potschka, Direct Multiple Shooting for parabolic PDE constrained optimization, in T. Carraro, M. Geiger, S. Körkel and R. Rannacher, editors, Multiple Shooting and Time Domain Decomposition Methods, volume 9 of Contributions in Mathematical and Computational Sciences, 159–181, Springer International Publishing, 2015
  • M. Behrens, H.G. Bock, S. Engell, P. Khobkhun, A. Potschka, Real-Time PDE Constrained Optimal Control of a Periodic Multicomponent Separation Process, In G. Leugering, P. Benner, S. Engell, A. Griewank, H. Harbrecht, M. Hinze, R. Rannacher, S. Ulbrich, editors, Trends in PDE Constrained Optimization, volume 165 of International Series of Numerical Mathematics, 521–537, Springer Basel, 2014
  • H.G. Bock, A. Potschka, S. Sager, and J.P. Schlöder, On the connection between forward and optimization problem in one-shot one-step methods, In G. Leugering, S. Engell, A. Griewank, M. Hinze, R. Rannacher, V. Schulz, M. Ulbrich, and S. Ulbrich, editors, Constrained Optimization and Optimal Control for Partial Differential Equations, volume 160 of International Series of Numerical Mathematics, 37–49, Springer Basel, 2012
  • A. Potschka, A. Küpper, J.P. Schlöder, H.G. Bock, and S. Engell, Optimal Control of Periodic Adsorption Processes: The Newton–Picard Inexact SQP Method, Recent Advances in Optimization and its Applications in Engineering, 361–378, Springer Verlag, 2010

Conference proceedings (with peer review)

  • R. Scholz, A. Nurkanovic, A. Mesanovic, J. Gutekunst, A. Potschka, H.G. Bock, E. Kostina, Model-based Optimal Feedback Control for Microgrids with Multi-Level Iterations, In J.S. Neufeld, U. Buscher, R. Lasch, D. Möst, and J. Schönberger, editors, Operations Research Proceedings 2019, Springer International Publishing, Cham, 73–79, 2020
  • D.H. Cebulla, C. Kirches, A. Potschka, Mixed-integer nonlinear PDE-constrained optimization for multi-modal chromatography, In J.S. Neufeld, U. Buscher, R. Lasch, D. Möst, and J. Schönberger, editors, Operations Research Proceedings 2019, Springer International Publishing, Cham, 81–87, 2020
  • D.H. Cebulla, C. Kirches, A. Potschka, Parameter Identifiability in a Novel Kinetic Adsorption Isotherm for Multi-Modal Chromatography, 2019 IEEE 58th Conference on Decision and Control (CDC), 4755–4760, 2019
  • H.C. La, A. Potschka, J.P. Schlöder, H.G. Bock, Dual Control and Information Gain in Controlling Uncertain Processes, 11th IFAC Symposium on Dynamics and Control of Process Systems Including Biosystems (DYCOPS-CAB) 2016, IFAC-PapersOnLine, 49(7):139–144, 2016
  • C. Lindscheid, D. Haßkerl, A. Meyer, A. Potschka, H.G. Bock, S. Engell, Parallelization of Modes of the Multi-Level Iteration Scheme for Nonlinear Model-Predictive Control of an Industrial Process, IEEE Multi-Conference on Systems and Control 2016, Control Applications (CCA), 1506–1512, 2016
  • D. Haßkerl, A. Meyer, N. Azadfallah, S. Engell, A. Potschka, L. Wirsching, H.G. Bock, Study of the Performance of the Multi-Level Iteration Scheme for Dynamic Online Optimization for a Fed-batch Reactor Example, European Control Conference (ECC) 2016, 459–464, 2016
  • C. Leidereiter, A. Potschka, H.G. Bock, Dual decomposition for QPs in scenario tree NMPC, Proceedings of the European Control Conference (ECC) 2015, 1608–1613, Linz, Austria, 2015
  • C. Leidereiter, A. Potschka, H.G. Bock, Quadrature-based scenario tree generation for Nonlinear Model Predictive Control, 19th World Congress of the International Federation of Automatic Control, Cape Town, South Africa, 19(1):11087–11092, 2014
  • M. Behrens, P. Khobkhun, A. Potschka, S. Engell, Optimizing Set Point Control of the MCSGP Process, 13th European Control Conference, Strasbourg, France, 1139–1144, 2014

Technical reports

  • A. Potschka, H.G. Bock, S. Engell, A. Küpper, and J.P. Schlöder, Optimization of Periodic Adsorption Processes: The Newton–Picard Inexact SQP Method, Preprint of DFG Priority Programme 1253: Optimization with Partial Differential Equations, SPP1253-01-01, 2008

Books

  • A. Potschka, A Direct Method for Parabolic PDE Constrained Optimization Problems, in H.G. Bock, W. Hackbusch, M. Luskin, R. Rannacher, editors, Advances in Numerical Mathematics, Springer Wiesbaden, 2014

Publicly understandable science

  • A. Potschka, Mathe Macchiato: Optimal trennen, Bild der Wissenschaft plus, 12–15, 2012

Theses

  • A. Potschka, Efficient numerical methods for large-scale nonlinear problems, Habilitationsschrift, Universität Heidelberg, 2017
  • A. Potschka, A direct method for the numerical solution of optimization problems with time-periodic PDE constraints, Dissertation, Universität Heidelberg, 2011
  • A. Potschka, Handling Path Constraints in a Direct Multiple Shooting Method for Optimal Control Problems, Diplomarbeit, Universität Heidelberg, 2006
 

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