Distributed Model Predictive Control Made Easy: Exploring Common Characteristics and Distinguishing Features
J. M. Maestre (University of Seville), R. R. Negenborn (Delft University of Technology), Carlos Ocampo Martínez (Technical University of Catalunya), Paul Trodden (University of Sheffield)

Ancillary Service from Flexible Loads to Help the Electric Grid of the Future
Prabir Barooah (University of Florida), Ian A. Hiskens (University of Florida), Anu Kowli (University of Illinois), Johanna L. Mathieu (ETH Zurich), Sean Meyn (University of Michigan)

Time Delay Systems: Theory, Numerics, and Analytical Approaches for Applications
Rifat Sipahi (Northeastern University, Boston), Fatihcan Atay (Max Planck Institute, Leipzig), Hitay Ozbay (Bilkent University, Ankara), Wim Michiels (Katholieke Universiteit Leuven), Silviu-Iulian Niculescu (CNRS LSS - Supélec)

Cooperative Distributed Control for Energy Management Systems: New Frameworks and Research Directions
Shinji Hara (University of Tokyo), Masayuki Fujita (Tokyo Institute of Technology)

Recent Advances in Semialgebraic Geometry: Applications in System Identification, Estimation and Filtering
Diego Regruto (Politecnico di Torino), Daniel E. Rivera (Arizona State University)

Dynamical Neural Systems, Synchronization and Control
Sridevi Sarma (Johns Hopkins University)

Intelligent Planning and Control: Bringing Together Adaptive Control and Reinforcement Learning for Guaranteeing Optimal Performance and Robustness
Girish Chowdhary (Oklahoma State University), Warren E. Dixon (University of Florida), Alborz Geramifard (Massachusetts Institute of Technology), Jonathan P. How (Massachusetts Institute of Technology), Eric N. Johnson (Georgia Institute of Technology), Frank L. Lewis (University of Texas Arlington), Tansel Yucelen (Georgia Institute of Technology), Thomas Walsh (Massachusetts Institute of Technology)

Relaxation Approaches for Control of Uncertain Complex Systems: Methodologies and Tools
Fabrizio Dabbene (CNR-IEIIT), Didier Henrion (LAAS CNRS), Dimitri Peaucelle (LAAS CNRS), Roberto Tempo (CNR-IEIIT)

Compressive Feedback Control Design for Spatially Distributed Systems
THIS WORKSHOP HAS BEEN CANCELED. Individuals who registered can either receive a full refund or transfer their registration to another workshop.

Distributed Control and Computing - Stability and Error-Correcting Codes
THIS WORKSHOP HAS BEEN CANCELED. Individuals who registered can either receive a full refund or transfer their registration to another workshop.

Distributed Model Predictive Control Made Easy: Exploring Common Characteristics and Distinguishing Features
Room VV 1.1

Organizers:
J. M. Maestre (University of Seville), R. R. Negenborn (Delft University of Technology), Carlos Ocampo Martínez (Technical University of Catalunya), Paul Trodden (University of Sheffield)

Abstract:

This workshop is divided in the following three parts:

In the first place, this workshop introduces the concept of Distributed Model Predictive Control (DMPC) and presents the key features of a DMPC scheme in a structured fashion. In particular, we present the two main type of DMPC schemes, classified according to the way in which the schemes are derived: either starting from a group of autonomous systems and then introducing communication to obtain coordination, or from a (hypothetical) monolithic system decomposed into subsystems that are coordinated taking into account limitations in communication/processing power. Undoubtedly, this is the most important feature in a DMPC scheme since it has to do with the perspective from which the distributed control scheme has been designed, bottom-up or top-down. Likewise, there is also a sensitive difference in the target applications of these two families of schemes.

The second part of the workshop deals with advanced topics about DMPC schemes. More specifically, we focus on how to improve the performance of DMPC schemes via supervision, negotiation or cooperation. Most theoretical results in DMPC have been concerned with achieving system-wide feasibility, stability and (to a lesser extent) robustness, but there are far fewer theoretical results on performance. Moreover, some of the conditions sufficient to guarantee feasibility/stability are harmful to performance. Likewise, we will study Coalitional MPC, a new type of DMPC scheme in which the local controllers only communicate when there is a noticeable increment in the system performance.

Finally, we conclude the workshop presenting benchmarks for the assessment of DMPC schemes in Matlab and providing the audience with hints regarding the evolution of Distributed MPC and potential research lines.

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Ancillary Service from Flexible Loads to Help the Electric Grid of the Future
Room VV G.4

Organizers:
Prabir Barooah (University of Florida), Ian A. Hiskens (University of Florida), Anu Kowli (University of Illinois), Johanna L. Mathieu (ETH Zurich), Sean Meyn (University of Michigan)

Abstract: The purpose of this workshop is to educate systems and control researchers about opportunities in enabling reliable operation of the future electric grid in the presence of large renewable penetration by harnessing the inherent flexibility in residential and commercial electric loads for providing ancillary services. The emphasis of the workshop is to make domain knowledge available to the audience so that those interested in conducting research can perform appropriate abstractions. In short, we will discuss more of "how it is now, what can be changed, what cannot be touched, what needs to be developed" rather than presenting a few models and control algorithms as gospel.

The expected audience includes engineers and scientists from industry and academia. The workshop will be self-contained so that it is suitable for systems and control researchers who may not have prior familiarity with the topics. The workshop audience is required to have an understanding of undergraduate-level control systems theory, basic circuits, and heat/mass transfer -- nothing more. The flow of the workshop is as follows:

1) the grid in transition,

2) introduction to power grid operation,

3) review of demand response today,

4) modeling & control problems related to flexible loads providing fast, intermediate, and slow timescale ancillary services, and

5) discussion & conclusions.

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Time Delay Systems: Theory, Numerics, and Analytical Approaches for Applications
Room VV G.2

Organizers:
Rifat Sipahi (Northeastern University, Boston), Fatihcan Atay (Max Planck Institute, Leipzig), Hitay Ozbay (Bilkent University, Ankara), Wim Michiels (Katholieke Universiteit Leuven), Silviu-Iulian Niculescu (CNRS LSS - Supélec)

Abstract: Time delays are all around us, from engineering and operations research, to biology, manufacturing, economics, and human-machine systems. When a feedback system is used to regulate the behavior of such systems, the appearance of delay in the control loop can be detrimental as the delay may cause the system to perform poorly, and to even become unstable. It is then an important question whether or not one can do something to prevent such undesirable behavior, perhaps by way of understanding how delays affect stability, the ability to control, and overall performance.

This workshop is offered to cover the very fundamentals of the above questions, from theory, numerical analysis, and applications points-of-views. In order to focus the workshop around a main theme, the organizers will discuss the basic concepts on Linear Time-Invariant Delay Systems, under the "frequency domain analysis" umbrella. The workshop will in particular focus on the following items:

(a) theoretical discussions on the existence and uniqueness of solutions, algebraic networks, interplay between networks and coupled dynamical systems, to stability of linear systems with single and multiple delays, their control, and inherent challenges,

(b) numerical approaches, including how one computes stability regions in parametric spaces, handles multiple-delay problems and control synthesis, and designs H-infinity controllers for delay systems, with coverage of inherent challenges and limitations,

(c) discussion of realistic applications ranging from simple to complex examples, including microscopic traffic flow dynamics, biological systems, inventory regulation problems in supply chains, network systems, tele-operation, and mechatronics systems.

The organizers will lecture in various formats, from slide presentations and basic blackboard derivations to computer simulations and videos of some results obtained from lab-scale experiments. Moreover, the lectures will be kept at an educational level, the audience will receive the presentation materials, and the organizers will interact with the audience to strengthen the effectiveness of the lectures.

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Cooperative Distributed Control for Energy Management Systems: New Frameworks and Research Directions
Room VV G.3

Organizers:
Shinji Hara (University of Tokyo), Masayuki Fujita (Tokyo Institute of Technology)

Additional Participants:
Jun-ichi Imura (Tokyo Inst. of Technology), Hideaki Ishii (Tokyo Inst. of Technology) Kameshwar Poolla (University of California at Berkeley), Jakob Stoustrup (Aalborg University), Yoshihiko Susuki (Kyoto University) Kenko Uchida (Waseda University),

Abstract: The main role of science and technology including control has shifted from realization of high quality products to solving crucial social problems such as energy, environment, and medicine. One of the exciting research topics in control community is to develop a new framework of control theory for total energy systems and provide systematic ways of designing energy management systems. Next generation energy network systems will incorporate significant amount of renewable energy sources, and the valuation of amount due to change of environments together with economic issues such as pricing as well as human issues should be carefully considered. Hence, for their efficient and safe operation, development of novel distributed energy management systems is crucial. To promote fundamental research in this direction, Japan Science and Technology Agency has initiated a CREST program named "Creation of fundamental theory and technology to establish a cooperative distributed energy management system and integration of technologies across broad disciplines toward social application."

This workshop is organized based on research activities in the CREST program cooperated with two distinguished people from USA and Europe in this area. It is divided into two parts, namely
(Part 1) A brief explanation of the background, idea, and outline of the CREST program followed by three overview type of presentations by Shinji Hara, Kameshwar Poolla, and Jakob Stoustrup on new research directions in control towards developing efficient and safe energy management systems.
(Part 2) Four presentations on new frameworks and recent results for several independent research topics: "Spatiotemporal-Resolved Supply/Demand Balancing for Huge-Scale Power Systems" by Jun-ichi Imura, "Optimal Integration Mechanism for Social Welfare Maximization for Energy Supply-demand Networks" by Kenko Uchida, "Analysis of Multi-Scale Multi-Energy Systems" by Yoshihiko Susuki, and "Distributed Intrusion Detection for Power Grids and Control Communication Networks" by Hideaki Ishii.

The main purposes of the workshop are to provide new frameworks of control system theory and research directions for analysis/synthesis of energy management systems, which are large-scale networked dynamical systems consisting of a variety of energy sub-systems as well as elements, and to show recent progress on several related research topics.

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Recent Advances in Semialgebraic Geometry: Applications in System Identification, Estimation and Filtering
Room VV 1.6

Organizers:
Diego Regruto (Politecnico di Torino), Daniel E. Rivera (Arizona State University)

Additional Participants:
Amir Ali Ahmadi (IBM Watson Research Center), Graziano Chesi (University of Hong Kong), Sunil Deshpande (Arizona State University), Håkan Hjalmarsson (KTH Royal Institute of Technology), Jean Bernard Lasserre (LAAS-CNRS and University of Toulouse), Pablo Parrilo (MIT), Mario Sznaier (Northeastern University)

Abstract: The proposed workshop is organized as part of the activities of the IEEE CSS Technical Committee on System Identification and Adaptive Control. By bringing together leading researchers from the fields of system identification and optimization, the organizers propose a set of tutorial lessons aimed at:

(i) reviewing the fundamental results and tools developed in the last decades in the field of semialgebraic geometry and polynomial optimization;

(ii) highlighting the potential of such results/tools to provide effective solutions to some challenging problems in the field of system identification, estimation and filtering

We believe that the proposed workshop will benefit the identification/control community as well as other communities, e.g., optimization, signal processing. All the contributors to this workshop are leading experts in the areas of identification/estimation and optimization. The potential audience of this workshop comprises a relatively large number of CDC participants.

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Dynamical Neural Systems, Synchronization and Control
Room VV 1.2

Organizer:
Sridevi Sarma (Johns Hopkins University)

Additional Participants:
Francesco Bullo (University of California at Santa Barbara), Antoine Chaillot (Supélec - Université Paris SUD), ShiNung Ching (Washington University in St. Louis), John Gale (Cleveland Clinic), Jeff Moehlis (University of California at Santa Barbara), Erwin B. Montgomery Jr. (University of Alabama), Rodolphe Sepulchre (Cambridge University)

Abstract: Synchronization phenomena in neuroscience are of great current interest particularly for information processing in nervous systems and neurological diseases. It is hypothesized that oscillations measured at the population level (e.g. local field potentials, EEG) may come from synchronized activity occurring at the neuronal level. In particular, oscillations have been shown to be important in the planning and generation of movements in healthy subjects. For example, when a subject is idle, prominent 10-30 Hz beta oscillations have been observed in motor cortical and subcortical structures; and when the subject begins planning a movement, these beta oscillations get suppressed and 50-90 Hz gamma band oscillations emerge. Therefore, beta oscillations have been termed "akinetic" while gamma band oscillations have been termed "prokinetic".
Interestingly, these oscillations also are observed (perhaps hijacked) in disease. For example, in Parkinson's disease, physiologists have reported increased synchronization and beta oscillations in the basal ganglia (nuclei affected by the loss of dopaminergic cells in the midbrain). These pathological neuronal signatures have been thought to play a role in motor symptoms observed in Parkinson's patients such as resting tremor, bradykinesia, and rigidity.

The goal of this workshop is to have an in-depth discussion on synchronization and oscillations in neural circuits - both in health and in disease. We would like to create an event where participants get a complete 360 degree picture of synchronization and oscillations in neural circuits and the role they play in information processing. Typically, such workshops are dominated by either mathematicians who look at networks of oscillators without regard to neurophysiology, or experimentalists who neglect mathematical models of observed phenomena. This workshop will include speakers from both communities in order to connect theory to reality in hopes of better understanding health and disease. The three subtopics this workshop will cover are:
1. Synchronization and pathological oscillations in neural circuits - in health and in Parkinson's disease - evidence from physiological experiments and computational models.
2. Theory on synchronization of oscillator networks (properties of networks that give rise to synchronization etc).
3. Performance measures and feedback control in Parkinson's disease (Deep Brain Stimulation control).

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Intelligent Planning and Control: Bringing Together Adaptive Control and Reinforcement Learning for Guaranteeing Optimal Performance and Robustness
Room VV G.1

Organizers:
Girish Chowdhary (Oklahoma State University), Warren E. Dixon (University of Florida), Alborz Geramifard (Massachusetts Institute of Technology), Jonathan P. How (Massachusetts Institute of Technology), Eric N. Johnson (Georgia Institute of Technology), Frank L. Lewis (University of Texas Arlington), Tansel Yucelen (Georgia Institute of Technology), Thomas Walsh (Massachusetts Institute of Technology)

Abstract: The problem of selecting the best set of decision actions in order to maximize the expected obtained cumulative reward is common to both biological and mechanical systems. Both autonomous planning and automatic control are concerned with choosing the right set of actions/inputs to maximize the obtained cumulative reward or minimize the incurred cumulative cost. At the heart of several control and planning algorithms are mathematical models that capture the underlying physical phenomena in various engineering applications. The challenge in solving this problem arises from uncertainties that are not captured by the available mathematical models; often introduced due to approximations made while deriving physical models from the first-principles, unforeseen increase in system complexity, time-variations, nonlinearities, disturbance, measurement noise, health degradation, and environmental uncertainties. Adaptive control is a leading methodology intended to guarantee stable high performance controllers in the presence of uncertainty. The problem of making decisions in the presence of uncertainties has also been widely studied in the planning literature. The typical approach there is to formulate these problems in the Markov decision processes (MDP) framework and search for the optimal policy. Solving MDPs without knowing the underlying model using reinforcement learning methods has become popular within the optimization community. The diminishing boundaries between individual fields of engineering and a greater emphasis on performance requirements of the system as a whole are bringing the problems of planning and control under uncertainties closer than ever. This has motivated several researchers to start searching for commonalities between adaptive control and reinforcement learning. The purpose of this workshop is to provide a detailed review of a number of well-established and emerging methods in both adaptive control and reinforcement learning by leading experts in the field. The goal is to create a venue for opening a pathway to merging ideas from these disciplines and allow for a unified presentation of the problem of planning and control under uncertainties in a data-rich world.

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Relaxation Approaches for Control of Uncertain Complex Systems: Methodologies and Tools
Room VV G.5

Organizers:
Fabrizio Dabbene (CNR-IEIIT), Didier Henrion (LAAS CNRS), Dimitri Peaucelle (LAAS CNRS), Roberto Tempo (CNR-IEIIT)

Abstract: The main objective of this workshop is to present recent developments and software tools in the areas of deterministic and probabilistic relaxation techniques for control of uncertain complex systems. After a tutorial introduction, the first part of the workshop discusses two successful paradigms, which are focused on polynomial optimization techniques and probabilistic randomized methods, respectively. These methodologies have been developed by researchers with diverse expertise. One of the objectives of this workshop is therefore to bring together two research communities, with the common objective to handle very general classes of uncertain systems by means of various software tools currently available.

The second part of the workshop is devoted to the description of the software tools GloptiPoly (Global optimization over polynomials), RoMulOC (Robust Multi-Objective Control) and RACT (Randomized Algorithms Control Toolbox). In particular, it will be demonstrated how classical control problems subject to "difficult" uncertainty structures can be effectively resolved with the techniques previously discussed. Finally, the efforts regarding integration of these tools into a unified package for control of uncertain systems subject to general classes of uncertainty will be described. Full information about the workshop is available at http://projects.laas.fr/CORARC.

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Compressive Feedback Control Design for Spatially Distributed Systems
CANCELED

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Distributed Control and Computing - Stability and Error-Correcting Codes
CANCELED

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