Katja Mombaur

Katja Mombaur is a full professor at the Institute of Computer Engineering of Heidelberg University and head of the Optimization, Robotics & Biomechanics Chair, as well as coordinator of the Heidelberg Center for Motion Research. She holds a diploma degree in Aerospace Engineering from the University of Stuttgart and a Ph.D. degree in Mathematics from Heidelberg University and has worked as a researcher at Seoul National University and in LAAS-CNRS in Toulouse. In 2020, she will join the University of Waterloo as Canada Excellence Chair for Human-Centered Robotics & Machine Intelligence. Her research focuses on understanding human movement by a combined approach of model-based optimization and experiments and using this knowledge to improve motions of humanoid robots and the interactions of humans with exoskeletons, prostheses and external physical devices.

The presentation on November 26, 2019 will be given in building 02, room 210 at the Otto-von-Guericke-University of Magdeburg and starts at 5.00 p.m..

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Paul Van Dooren

Professor of Mathematical Engineering

Université Catholique de Louvain, Belgium

The presentation on October 22nd, 2019 will be given in the Lukasklause (Schleinufer 1, 39104 Magdeburg) and starts at 5.00 p.m..

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Theory and Experiments

Prof. Paolo Falcone

Department of Electrical Engineering

Chalmers University of Technology

Gothenburg, Sweden

The presentation on May 14, 2019 will be given in building 10, room 460 at the Otto-von-Guericke-University of Magdeburg and starts at 5.00 p.m..

The next challenge, beyond high-level autonomous driving, is the coordination of autonomous vehicles, which is expected to fully enable the potential of autonomous driving technologies and heavily impact the society. Nevertheless, the safety and performance issues arising from the tight coupling between information losses and delays and the control system stability and performance must be accounted for at the design stage. Starting from a multi-vehicle coordination problem at traffic junctions, which has been experimentally demonstrated relying on both the IEEE 802.11p wireless standard and a 5G cellular network prototype, we will motivate a joint communication and control paradigm, where a central coordinator decides upon control inputs to a set of dynamical systems and their access to the communication channel. We will show a few results from numerical examples and new research directions.

Short CV

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Prof. Dr. Andrea Walther

Institut für Mathematik

Universität Paderborn

The presentation on November 6, 2018 will be given in the Lukasklause (Schleinufer 1, 39104 Magdeburg) and starts at 5.00 p.m..

The complete design chain in Computational Fluid Dynamics (CFD) covers the parameterization of the object to be optimized like, e.g., an air foil, the usage of a Computer Aided Design (CAD) tool to actually construct the air foil and a flow solver to compute the flow around the air foil. The optimization of such a complete design chain that includes a CAD tool is still a severe challenge. In this talk we present the technique of algorithmic differentiation (AD) to compute exact derivative information for a given simulation code. We discuss how AD can be applied to the CAD kernel within OpenCASCADE Technology and a suitable flow solver taking also the complexity of the derivative information into account. We will see that a gradient-based optimization using adjoint information is the only tractable way. First numerical results for the optimization of a U-bend pipe used frequently as a cooling channel and of the TU Berlin stator as one example from turbo machinery are shown. This includes also a verification of the computed derivatives.

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Prof. Dr. Marc Pfetsch

TU Darmstadt

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Gabriele Pannocchia

Associated Professor,

Department of Civil and Industrial Engineering,

University of Pisa

The presentation on March 19, 2018 will be given at the Otto-von-Guericke-University Magdeburg, Universitätsplatz 2, building 7 - room 208 and starts at 5 p.m..

Optimization based strategies for planning and feedback control represent a general framework of numerical methods in which a (often deterministic) model of the system under consideration and its environment are exploited to achieve high-level goals (e.g., minimization of energy consumption, emission of pollutants, maximization of throughput, etc.) as well as more specific tasks (e.g. product quality control, robotic manipulation), while respecting a number of constraints arising from physical, safety or performance limits.

In this seminar, I review and analyze the main concepts, successes and ongoing challenges of optimization based methods, with a particular emphasis on how uncertainties can be dealt with effectively and efficiently using disturbance estimation techniques. During the seminar, I present several examples ranging from reaction processes to robotic systems.

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Prof. dr. ir. Jacquelien M.A. Scherpen

University of Groningen

The presentation on January 23, 2018 will be given in the Max Planck Institute Magdeburg, Großer Seminarraum 'Prigogine' and starts at 5.00 p.m..

In this talk I will first give a combined distributed, hierarchical optimal control perspective using dual decomposition and pricing mechanisms for smart energy systems, and in particular for household prosumers (consumers and producers). In this setup a possible future (EU) market structure is taken into account. Furthermore, I will take a second perspective from the physics, where stabilisation is important, and optimisation is done on the welfare function. Some questions about the coupling of these two perspectives are raised.

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Prof. Dr. Arthur Krener

Naval Postgraduate School, Monterey

The presentation on November 6, 2017 will be given in the Senatssaal (G05) and starts at 5.00 p.m..

Minimum Energy Estimation is a way of filtering the state of a nonlinear system from partial and inexact measurements. It is a generalization of Gauss' method of least squares. Its application to filtering of control systems goes back at least to Mortenson who called it Maximum Likelyhood Estimation \cite{Mo68}. For linear, Gaussian systems it reduces to maximum likelihood estimation (akaKalman Filtering) but this is not true for nonlinear systems. We prefer the name Minimum Energy Estimation (MEE) that was introduced by Hijab \cite{Hi80}. Both Mortenson and Hijab dealt with systems in continuous time, we extend their methods to discrete time systems and show how power series techniques can lessen the computational burden.

Moving Horizon Estimation (MHE) is a moving window version of MEE. It computes the solution to an optimal control problem over a past moving window that is constrained by the actual observations on the window. The optimal state trajectory at the end of the window is the MEE estimate at this time. The cost in the optimal control problem is usually taken to be an L2 norm of the three slack variables; the initial condion noise, the driving noise and the measurement noise. MHE requires the buffering of the measurements over the past window. The optimal control problem is solved in real time by a nonlinear program solver but it becomes more difficult as the length of the

window is increased.

The power series approach to MME can be applied to MHE and this permits the choice of a very short past window consisting of one time step. This speeds up MHE and allows its real time implementaion on faster processes. We demonstrate its effective on the chaotic Lorenz attractor.

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Prof. Dr. Christoph Helmberg

TU Chemnitz

The presentation on October 24, 2017 will be given in the Festung Mark (oberes Gewölbe) and starts at 5.00 p.m..

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Prof. Dr. Bernd Gärtner

ETH Zürich, Schweiz

The presentation on May 30, 2017 will be given in the Lukasklause (Schleinufer 1, 39104 Magdeburg) and starts at 5.00 p.m. (Historischer Raum).

Given a network with origin and destination, what is the complexity of deciding whether the train, starting at the origin, will eventually reach the destination?

It is easy to see that this problem can be solved in exponential time, but we are not aware of any polynomial-time method. In this talk, I explain where the problem comes from and prove that is is in NP ∩ coNP; actually in UP ∩ coUP (problems with unique NP/coNP certificates).

This raises the question whether people have so far just failed to find a (simple) polynomial-time solution, or whether the complexity status is more subtle, as for some other well-known (two-player) graph games.

Joint work with Jérôme Dohrau, Hagar Mosaad, Manuel Kohler, Jiří Matoušek, Emo Welzl

Prof. Dr. Claudia Schillings

Universität Mannheim

The presentation on June 27, 2017 will be given in the Lukasklause (Schleinufer 1, 39104 Magdeburg) and starts at 5.00 p.m. (Großer Saal).

Prof. Dr. Mirjam Dür

Department of Mathematics

University of Trier

The presentation on December 13, 2016 will be given in the Carnot-Gebäude G25 in Room 201 and starts at 5.00 p.m..

The lecture is part of the 10th CDS anniversary.

Prof. Dr. Manfred Morari

Distinguished Faculty Fellow

University of Pennsylvania

The presentation on October 18, 2016 will be given in the Lukasklause (Schleinufer 1, 39104 Magdeburg) and starts at 5.00 p.m. (Historischer Raum).

Manfred Morari was head of the Department of Information Technology and Electrical Engineering at ETH Zurich from 2009 to 2012 and head of the Automatic Control Laboratory from 1994 to 2008. Before that he was the McCollum-Corcoran Professor of Chemical Engineering and Executive Officer for Control and Dynamical Systems at the California Institute of Technology. From 1977 to 1983 he was on the faculty of the University of Wisconsin. He obtained the diploma from ETH Zurich and the Ph.D. from the University of Minnesota, both in chemical engineering. His interests are in constrained and robust control. Morari’s research is internationally recognized. The analysis techniques and software developed in his group are used in universities and industry throughout the world. He has received numerous awards, including the Eckman Award, Ragazzini Award and Bellman Control Heritage Award from the American Automatic Control Council; the Colburn Award, Professional Progress Award and CAST Division Award from the American Institute of Chemical Engineers; the Control Systems Technical Field Award and the Bode Lecture Prize from IEEE. He is a Fellow of IEEE, AIChE and IFAC. In 1993 he was elected to the U.S. National Academy of Engineering and to the UK Royal Academy of Engineering in 2015. He served on the technical advisory boards of several major corporations.

Prof. Dr. Britta Peis

RWTH Aachen University

Chair of Management Science

The presentation on October 25, 2016 will be given in the Lukasklause (Schleinufer 1, 39104 Magdeburg) and starts at 5.00 p.m. (Historischer Raum).

Prof. Dr. Zlatko Drmac

University of Zagreb

Accurate linear algebra in computational

methods for system and control theory

Lukasklause, Schleinufer 1

Jointly organized by: Faculty of Electrical Engineering and Information Technology, Faculty of Mathematics, Max Planck Institute Magdeburg Center for Dynamic Systems: Biosystems Engineering

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Prof. Dr. Anton Schiela

University of Bayreuth

The presentation on January 12, 2016 will be given at the Lukasklause, Schleinufer 1, Magdeburg and starts at 5.00 p.m.

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Prof. Dr. Samuel Fiorini

Université Libre de Bruxelles

The presentation on December 8, 2015 will be given at the Lukasklause, Schleinufer 1, Magdeburg and starts at 5.00 p.m.

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Prof. Greg Blekherman, Ph.D.

Georgia Tech

The presentation on June 30, 2015 will be given in the Otto-von-Guericke-University Magdeburg G03-214 and starts at 5.00 p.m.

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Matthias Heinkenschloss

Department of Computational and Applied Mathematics

Rice University

The presentation on June 29, 2015 will be given in the Lukas Klause (Schleinufer 1, 39104 Magdeburg) and starts at 5.00 p.m.

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Dr. Benoit Chachuat

Faculty of Engineering

Centre for Process Systems Engineering

Department of Chemical Engineering

Imperial College London

UK

The presentation on June 29, 2015 will be given in the Senatssaal (building 05, room 205) and starts at 5.00 p.m.

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Prof. Dr. Harry L. Trentelman

Johann Bernoulli Institute for Mathematics and Computer Science

University of Groningen

The Netherlands

The presentation on April 16, 2015 will be given in the Lukasklause (Schleinufer 1, 39104 Magdeburg) and starts at 5.00 p.m.

This talk deals with the problem of model reduction of multi-agent systems defined on a graph. Reduced order models are obtained by clustering the vertices (agents) of the underlying communication graph by means of suitable graph partitions. In the reduction process the spatial structure of the network is preserved and the reduced order models can again be realized as multi-agent systems defined on a graph. The agents are assumed to have single-integrator dynamics and the communication graph of the original system is weighted and undirected. The proposed model reduction technique reduces the number of vertices of the graph (which is equal to the dynamic order of the original multi-agent system) and yields a reduced order multi-agent system defined on a new graph with a reduced number of vertices. This new graph is a weighted symmetric directed graph. It is shown that if the original multi-agent system reaches consensus, then so does the reduced order model. For the special case that the clusters are chosen using an almost equitable partition of the graph, we obtain an explicit formula for the H-2 norm of the error system obtained by comparing the input-output behaviors of the original model and the reduced order model. We also prove that the error obtained by taking an arbitrary partition of the graph is bounded from below by the error obtained by using the largest almost equitable partition finer than the given partition. Finally, we extend our results on single integrator dynamics to the case that the agent dynamics is an arbitrary linear input-output system.

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Prof. Jan Maciejowski

Dep. of Engineering

University of Cambridge

UK

The presentation on January 27, 2015 will be given in the Senatssaal (building 05, room 205) and starts at 5.00 p.m.

Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control. Some remarks will be made about the use of a Bayesian framework for studying fault-tolerant control.

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The presentation on December 9, 2014 will be given in the Lukasklause (Schleinufer 1, 39104 Magdeburg) and starts at 5.00 p.m.

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The presentation on November 4, 2014 will be given in the Lukas Klause (Schleinufer 1, 39104 Magdeburg) and starts at 5.00 p.m.

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The presentation on June 16, 2014 will be given at the Otto-von-Guericke-Universität Magdeburg, Universitätsplatz 2, building 03 - room 106 and starts at 4.45 p.m.

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The presentation on June 26, 2014 will be given at the Otto-von-Guericke-Universität Magdeburg, Universitätsplatz 2, building 2 - room 210 and starts at 4 p.m.

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