Speakers

ECC brings Europe's systems control experts together to share their work through presentations and workshops.

Plenary Speakers

Semi-Plenary Speakers

Tutorial Organizers

Dimitris Bertsimas
Video

Tariq Samad
Video

Ron Weiss
Video

Duncan Callaway
Video

Marco Campi
Video

Hartmut Geyer
Video

Holger Hermanns
Video

Damon Vander Lind
Video

Glenn Vinnicombe
Video coming soon.

Bo Wahlberg

Colin Jones
Michal Kvasnica
Martin Herceg

Daniel Kuhn
Karthik Natarajan

Ian Hiskens

Alexandre Bayen
Jack Reilly

Henrik Sandberg
Bruno Sinopoli

Heinz Koeppl

Tutorial Overview
(106 KB PDF)


Plenary Speakers


Dimitris Bertsimas

Dimitris Bertsimas
Sloan School of Management
Massachusetts Institute of Technology
USA

Dimitris Bertsimas is currently the Boeing Leaders for Global Operations Professor of Management and the co-director of the Operations Research Center at the Massachusetts Institute of Technology. He has received a BS in Electrical Engineering and Computer Science at the National Technical University of Athens, Greece in 1985, a MS in Operations Research at MIT in 1987, and a Ph.D. in Applied Mathematics and Operations Research at MIT in 1988. Since 1988, he has been in the MIT faculty. His research interests include optimization, stochastic systems, data mining, and their applications.

In recent years he has worked in robust optimization, health care analytics. He has published over 150 papers and 3 graduate level textbooks. He is a member of the National Academy of Engineering and he has received several research awards including the Farkas prize, the SIAM Optimization prize and the Erlang Prize. He has supervised 50 doctoral students at MIT and he is currently supervising 12 others.

Dimitris Bertsimas:

A computationally tractable theory of performance analysis in stochastic systems

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Modern probability theory, whose foundation is based on the axioms set forth by Kolmogorov, is currently the major tool for performance analysis in stochastic systems. While it offers insights in understanding such systems, probability theory is really not a computationally tractable theory. Correspondingly, some of its major areas of application remain unsolved when the underlying systems become multidimensional: Queueing networks, network information theory, pricing multi-dimensional financial contracts, auction design in multi-item, multi-bidder auctions among others.

We propose a new approach to analyze stochastic systems based on robust optimization. The key idea is to replace the Kolmogorov axioms as primitives of probability theory, with some of the asymptotic implications of probability theory: the central limit theorem and law of large numbers and to define appropriate robust optimization problems to perform performance analysis. In this way, the performance analysis questions become highly structured optimization problems (linear, conic, mixed integer) for which there exist efficient, practical algorithms that are capable of solving truly large scale systems.

We demonstrate that the proposed approach achieves computationally tractable methods for (a) analyzing multiclass queueing networks, (b) characterizing the capacity region of network information theory and associated coding and decoding methods generalizing the work of Shannon, (c) pricing multi-dimensional financial contracts generalizing the work of Black, Scholes and Merton, (d) designing multi-item, multi-bidder auctions generalizing the work of Myerson.

This is joint work with my doctoral student at MIT Chaithanya Bandi.

Tariq Samad

Tariq Samad
Honeywell Automation and Control Solutions
Minneapolis
USA

Tariq Samad is Corporate Fellow at Honeywell Automation and Control Solutions, in Minneapolis, U.S.A. During his 27 years with Honeywell he has contributed to and led automation and control developments for applications in electric power systems, the process industries, building management, automotive engines, unmanned aircraft, and clean energy. His research interests relate broadly to automation, intelligence, and autonomy for complex engineering systems.

Dr. Samad served as President of IEEE Control Systems Society in 2009 and is President Elect of the American Automatic Control Council. He is an IEEE Fellow and the recipient the 2008 IEEE CSS Control Systems Technology Award and other distinctions. He was editor-in-chief of IEEE Control Systems Magazine during 1998 – 2003 and General Chair for the 2012 American Control Conference. His recent publications include The Impact of Control Technology. Dr. Samad holds a B.S. from Yale University and M.S. and Ph.D. degrees from Carnegie Mellon University.

Tariq Samad:

Control for smart grids: Applications and opportunities in the customer domain

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One of the principal points of differentiation between smart grids and traditional power systems is the importance the former accord to electricity consumers and customers-residential, commercial, and industrial facilities are an integral part of the smart grid system of systems. Furthermore, the portfolio of energy assets in homes, buildings, and factories is being dramatically enhanced; distributed generation and storage, in addition to heterogeneous loads and in grid-connected implementations, manifest that “demand-side” management is not just about demand any longer.  Realizing the smart grid vision of clean, low-cost, and securely supplied energy depends crucially on the active engagement of facility owners, operators, and assets. With measurement, communication, and computing becoming pervasive in the expanded end-to-end electricity infrastructure, the stage is set for control technologies. Notable progress has been made already. Several innovative and exciting projects are under way worldwide and significant economic and societal benefits have been achieved, especially in areas such as automated demand response, optimal microgrids, and energy analytics. Yet we have just scratched the surface of possibility. Faster dynamics, larger-scale systems, more diverse assets, dynamic pricing, humans in the loop, and other complexities and trends all suggest opportunities for control research with the promise of tremendous impact on society and industry.

Ron Weiss

Ron Weiss
Department of Biological Engineering
Massachusetts Institute of Technology
USA

Ron Weiss is an Associate Professor in the Department of Biological Engineering and the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. Weiss received his PhD from MIT in 2001 and currently serves as the Director of MIT's newly formed Synthetic Biology Center. His research focuses on synthetic biology, where he programs cell behavior by modeling and experimentally constructing artificial cellular pathways. A major thrust of his work is the synthesis of gene networks that are engineered to perform in vivo analog and digital logic computation. He is also interested in programming cell aggregates to perform coordinated tasks using engineered cell-cell communication. He has constructed and tested several novel in vivo biochemical logic circuits and intercellular communication systems in bacteria and yeast. More recently, the Weiss lab has focused on mammalian synthetic biology and several therapeutic application areas including programmed tissue engineering, diabetes, and cancer.

Ron Weiss:

Synthetic biology: From parts to modules to therapeutic systems

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Synthetic biology is revolutionizing how we conceptualize and approach the engineering of biological systems. Recent advances in the field are allowing us to expand beyond the construction and analysis of small gene networks towards the implementation of complex multicellular systems with a variety of applications. In this talk I will describe our integrated computational / experimental approach to engineering complex behavior in living systems ranging from bacteria to stem cells. In our research, we appropriate design principles from electrical engineering and other established fields. These principles include abstraction, standardization, modularity, and computer aided design. But we also spend considerable effort towards understanding what makes synthetic biology different from all other existing engineering disciplines and discovering new design and construction rules that are effective for this unique discipline. We will briefly describe the implementation of genetic circuits and modules with finely-tuned digital and analog behavior and the use of artificial cell-cell communication to coordinate the behavior of cell populations. The first system to be presented is a genetic circuit that can detect and destroy specific cancer cells based on the presence or absence or specific biomarkers in the cell. We will also discuss preliminary experimental results for obtaining precise spatiotemporal control over stem cell differentiation for tissue engineering applications. We will conclude by discussing the design and preliminary results for creating an artificial tissue homeostasis system where genetically engineered stem cells maintain indefinitely a desired level of pancreatic beta cells despite attacks by the autoimmune response, relevant for diabetes.


Semi-Plenary Speakers


Duncan Callaway

Duncan Callaway
Energy and Resources Group
University of California
Berkeley
USA

Duncan Callaway
received his PhD in Theoretical and Applied Mechanics and Applied Mathematics from Cornell University in 2001 and subsequently held an NSF Postdoctoral Fellowship and spent 4 years working in the energy industry. He was a member of the research faculty at the University of Michigan from 2006-2009 and joined UC Berkeley as an assistant professor of Energy and Resources in the Fall of 2009. Dr. Callaway's teaching focuses on power systems and energy efficiency. His research focuses on modeling and control of distributed energy resources and identification of energy efficiency opportunities in buildings from large data sets. Some of the specific application areas he works on include wind energy, demand response and load control, plug-in electric vehicles and building controls.

Duncan Callaway:

Demand-side modeling, estimation and control in electric power systems

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For over a century, one of the central objectives in power system operation and control has been to balance constantly varying electricity demand. Currently, a suite of decentralized and centralized control actions on the supply side is used to manage expected and unexpected changes in demand. Now, however, the supply side is becoming part of the problem, as increasing amounts of wind and solar technologies are added to the grid with variability and uncertainty that easily exceeds that of demand. How will these new challenges be met? An interesting possibility is to make the demand side part of the solution by exploiting latent flexibility in electricity consumption patterns. Quite simply, this means consuming more electricity when wind or solar power is available, and less when unavailable. But, of course, the devil is in the details.

This talk will cover recent efforts to understand if and how system operators can elicit power system flexibility by engaging the demand side. The central control challenge is that end-use function (e.g. thermal comfort, battery state of charge, illumination) is often at odds with system-level objectives to balance real power supply and demand. Balancing these competing objectives first requires models that adequately describe the end-use process but are sufficiently general to be easily parameterized and included in model-based control schemes.  I will discuss these modeling issues and results from my group and others’, with extensive discussion on the role of statistical aggregation. I will then discuss recent research results to highlight the tradeoffs of different control architectures – ranging from completely centralized to fully decentralized – with emphasis on integration into legacy system operations and the cyber-physical systems perspective. Finally I will discuss the importance of models and control system design on the challenge of estimating the size of flexible demand resources.


Marco Claudio Campi

Marco Campi
Department of Electronics for Automation
University of Brescia
Italy

Marco Claudio Campi is a Professor of Automatic Control at the University of Brescia, Italy. From 1989 to 1992, he was a Research Fellow at the Centro di Teoria dei Sistemi of the National Research Council (CNR) in Milano and, in 1992, he joined the University of Brescia, Brescia, Italy. He is the chair of the Technical Committee IFAC on Modeling, Identification and Signal Processing (MISP), has been in various capacities on the Editorial Board of Automatica , Systems and Control Letters and the European Journal of Control, and has served as a distinguished lecturer of the Control Systems Society. In 2008, he received the IEEE CSS George S. Axelby outstanding paper award for the article The Scenario Approach to Robust Control Design. Marco Campi is a Fellow of IEEE, a member of IFAC, and a member of SIDRA. His interests include: data-based optimization, randomized methods, system identification, and learning theory.

Marco Campi:

The scenario approach to stochastic optimization

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Many design problems in control, identification and signal processing can be expressed as optimization problems. In many cases, the environment in which the optimization is performed contains uncertain elements, and the designer acquires knowledge about uncertainty through experience, that is, by looking at previous cases, or “scenarios”, of the same problem. This is the set-up in which the scenario approach operates. The scenario approach has a practical appeal due to its simplicity. On the other hand, it is also a mathematically solid method whose justification is grounded on a rigorous generalization theory.

In the talk, we shall introduce the scenario approach, and explore some of its potentials and properties.

Hartmut Geyer

Hartmut Geyer
Robotics Institute
Carnegie Mellon University
Pittsburgh
USA

Hartmut Geyer
received the Dipl. degree in Physics and the Ph.D. degree in Biomechanics from the Friedrich-Schiller-University of Jena in 2001 and 2005, respectively. He is currently an Assistant Professor at the Robotics Institute of Carnegie Mellon University. Prior to joining Carnegie Mellon, he held an EU Marie Curie Fellowship and worked as a postdoctoral researcher at the MIT Biomechatronics Group and at the Institute for Automatic Control of ETH Zurich. His research focuses on the principles of legged dynamics and control, their relation to human motor control, and resulting applications in humanoid and rehabilitation robotics.

Hartmut Geyer:

Legged dynamics and control: Basic models, neuromuscular interpretation, and robotic application

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Legged mobility forms one of the great challenges and opportunities to scientific understanding and technological development. One day, legged machines will help humans in everyday mobility tasks and powered exoskeletons and prostheses will seamlessly enhance, restore or replace the functionality of human legs. At present however much of the science of legged dynamics and control still needs to be discovered, and much of the technology, to be developed. This talk presents one specific approach toward this goal that emphasizes the inherent connection between the basic physics of legged systems, human neuromuscular control, and technological solutions in robotics.

The talk is organized in three parts. First, we review basic models of legged dynamics and control. We then address how their systematic interpretation with spinal reflexes leads to neuromuscular models which predict human muscle activations and generate a variety of human locomotion behaviors such as walking, running, obstacle avoidance, and stair climbing. Finally, we present work on technological solutions in humanoid and rehabilitation robotics that is inspired by the control strategies identified in the basic and neuromuscular models.

Holger Hermanns

Holger Hermanns
Dependable Systems and Software
Saarland University
Saarbr├╝cken
Germany

Holger Hermanns is a full professor in the Department of Computer Science at Saarland University, Saarbr├╝cken, Germany, holding the chair for Dependable Systems and Software. His research interests include modeling and verification of concurrent systems, resource-aware embedded systems, and compositional performance and dependability evaluation, including dependable energy distribution grids. In these areas, Holger Hermanns has authored or co-authored more than 150 peer-reviewed scientific papers, has co-chaired the program committees of major international conferences such as TACAS 2006, CONCUR 2006, CAV 2007, and QEST 2012. He serves on the steering committees of ETAPS and QEST, and has authored a monograph in the LNCS series of Springer-Verlag on interactive Markov chains. He received the Dutch national innovation award, is a founding member and principal investigator of the German special research initiative SFB AVACS, coordinator of the EU FP7 project MEALS, and holder of several other national and European research grants.

Holger Hermanns:

Power grid stability despite renewable instability

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The electric power grids across Europa are evolving towards decentralized structures, rooted in political decisions to counter the worldwide climate change. Especially the German power grid is facing the disruptive challenge to integrate massive decentral infeed of renewable electric power. This implies drastically higher volatility in available electric power, which in turn is a threat to power grid stability across the entirety of continental Europe.


This presentation discusses the challenge as a large-scale distributed control problem. We derive a set of principles that inspire the design of a new generation of distributed and decentralised power grid control appliances. We report on controller designs for masses of microgenerators, and contrast their reliable operation with critical shortcomings of controllers installed on hundreds of thousands of German rooftops to date. While doing so, we discuss a modelling and verification technology revolving around stochastic hybrid automata, employed to validate and evaluate these controllers.

Damon Vander Lind

Damon Vander Lind
Makani Power Inc.
Alameda, California
USA

Damon Vander Lind leads the engineering team at Makani Power. He holds degrees in physics and electrical engineering/computer science from MIT. He has been responsible for many developments at Makani, including the highly stable flight vehicle configuration flown today, quiet hybrid turbine/propeller blades, a robust predictive path controller, and various aerodynamic, electromechanical, and structural elements of the system which have led to numerous patents pending.

Damon Vander Lind:

The design and control of airborne wind turbines

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Wind power has seen tremendous growth over the past decade. However, conventional turbine technology has largely matured. It is unlikely to see substantial cost reductions as turbine cost is largely dictated by the cost of structural materials, and the levelized cost of wind energy has in fact increased over this timeframe. Continued breakout growth for the sector will depend upon truly disruptive innovation that expands the developable resource while significantly reducing cost. Makani's Airborne Wind Turbine offers these advantages, generating 50% more energy, while using 10% of the materials of conventional turbines per unit of capacity. In effect, Makani is replacing steel and fiberglass with computation, both in the way the flight system is controlled, and in the way the system is designed. We will look at the mechanisms through which design and control interact to yield a robust system capable of elegantly responding to high winds, turbulence, and component failures.

Glenn Vinnicombe

Glenn Vinnicombe
Department of Engineering
University of Cambridge
UK

Glenn Vinnicombe graduated with a BA in Engineering from Cambridge in 1984. From 1984 to 1987 he was with British Aerospace, working primarily on the design and flight test of control systems on the Airbus A320. He returned to Cambridge in 1987 as a College Lecturer at Churchill College, obtaining the PhD degree in 1993. He has held faculty positions at the Department of Mechanical Engineering, University of Minnesota, and in the Department of Aeronautical Engineering, Imperial College, London and is currently a Reader in Control Engineering at the University of Cambridge, Department of Engineering. His current research is primarily concerned with design principles for feedback regulation in networks (particularly communication and power distribution) and biological systems.

Glenn Vinnicombe:

Information processing and control in biological systems; some fundamental limits

Video coming soon.

Many biological processes, from insect vision to gene regulation, are constrained by the effects of delays and small numbers. There are many different ways of attempting to quantify this. In order to rigorously capture the limitations, to keep us honest, we choose to look at their impact on the system's ability to solve causal estimation and control problems. Models of biological systems are, at best, sparsely characterised; with large margins of error even then. Our general approach is to assume that some observable aspects of the sensing or regulatory network are known and to then abstract away the rest of the network by optimising over it. What is the best that nature could be doing, given the constraints it is acting under? For the regulation of copy numbers of molecules in the cell we will show that the limitations imposed by delays in response or by small numbers of signalling molecules are severe, particularly when they occur in combination. For insect vision, an understanding of the fundamental limitations in early visual processing leads to a better understanding of more complex problems. We propose this approach as a new way of studying biological dynamics; where lack of knowledge need not prevent us from saying some things with confidence.