The ECC offers workshops addressing current and future topics in control systems from experts from academia, research institutes, and industry. Workshops emphasizing tutorial expositions of emerging theory and applications are encouraged.

The workshops are held at the conference venue on June 28th, 2016, the day before the official opening of the conference. Please contact the Workshops Chair, Tariq Samad, or the Tutorial Sessions Chair, Rodolphe Sepulchre, for further details.

Advance registration for pre-conference workshops will be done through the conference registration website. On-site registration at the conference venue will also be available. Please note that workshops are (a) subject to cancellation for lack of registrants, and (b) subject to capacity limits.

Workshop 1: Distributed and Stochastic Optimization: Theory and Applications


Kostas Margellos, University of Oxford, U.K.
Maria Prandini, Politecnico di Milano, Italy

Additional speakers

Angelia Nedich, University of Illinois at Urbana-Champaign, U.S.
Luca Schenato, University of Padova, Italy
Giuseppe Notarstefano, University of Salento, Italy
Olaf Stursberg, University of Kassel, Germany
Karl Henrik Johansson, KTH Stockholm, Sweden
Christoforos Hadjicostis, University of Cyprus, Cyprus
Florian Dörfler, ETH Zurich, Switzerland
Saverio Bolognani, ETH Zurich, Switzerland


The aim of the workshop is to provide a concise, yet complete, exposition to the topic of distributed and stochastic optimization, with an in-depth understanding of the mathematical and algorithmic mechanisms underlying it, of the potential communication and computational savings of such implementations, and of how uncertainty can be dealt with in a rigorous manner. This comprehensive introduction to the machinery underlying distributed and stochastic optimization will encourage the development of new results and the investigation of several important issues in the future of distributed optimization and control over uncertain networks.

Merging distributed optimization algorithms with stochastic optimization techniques that allow for a rigorous treatment of uncertainty is a challenging problem. We anticipate the workshop to expose attendees to recent algorithmic developments covering a wide spectrum of theoretical topics, as well as to applications of contemporary interest like smart grid monitoring and control, control of cyber-physical systems, and wireless networks.

The workshop aims to attract graduate students and researchers with an interest in optimization-based control, to get them exposed to the fundamentals of distributed and stochastic optimization, and to point out recent advancements and open research directions in the field. The target audience also includes researchers who are more inclined towards applications rather than only theoretical aspects. Emphasis will be given on illustrating the potential of applying the theoretical machinery to different problems in the energy sector, highlighting its importance in transitioning from centralized power management to smart-grid control concepts, and facilitating the integration of intermittent energy sources like renewables.

Program (tentative)

  • Distributed Learning in Graphs – Angelia Nedich
  • Proximal algorithms for distributed optimization over uncertain networks – Kostas Margellos
  • Distributed convex optimization algorithms robust to asynchronous computation and lossy communication – Luca Schenato
  • Constraint-exchange methods for robust distributed optimization in asynchronous networks – Giuseppe Notarstefano
  • Model Predictive Control for Jump-Markov-Linear Systems – Olaf Stursberg
  • Scenario-based model predictive control applied to building automation systems – Karl Henrik Johansson
  • Distributed Control Approaches in Emerging Electrical Energy Systems – Christoforos Hadjicostis
  • An optimization-on-manifold approach to the design of distributed feedback control in smart grids – Florian Dorfler

Click here for more information about the workshop.

Workshop 2: Optimization and Control for Tomorrow’s Power Systems


Ulrich Münz, Siemens Corporate Technology, Germany
Florian Dörfler, ETH Zürich, Switzerland
Johannes Schiffer, University of Leeds, U.K.

Additional speakers

Marco Cupelli, RWTH Aachen, Germany
Gabriela Hug, ETH Zürich, Switzerland
Na Li, Harvard University, U.D.
Francesco Vasca, University of Sannio, Italy
Remus Teodorescu, Aalborg University, Denmark


The increasing penetration of distributed and renewable generators into today’s power systems poses new challenges to power system management and control. Future power system management systems have to balance the mismatch between volatile renewable generation and load as well as to bridge the geographical gap between renewable generators and load centers. For power system modeling, analysis and control, the mathematical and physical fundamentals of state-of-the-art methods have to be questioned in general, because these methods rely on power supply through synchronous generators and most renewable generators are connected to the power system with power electronic converters.

The major topics covered in the workshop are economic dispatch and unit commitment, power flow optimization, power system stability and control, as well as modeling and control of power electronic converters. For each topic, selected experts will present their recent findings. We aim at a stimulating and interactive environment leaving plenty of time for discussions among workshop attendees and speakers.

The workshop is intended both for experts in and newcomers to this field. It provides a unique opportunity to get a broad and profound overview of recent developments in all fields of power system control and optimization as well as to have a close interaction with the presenters. A basic knowledge of electrical engineering and power systems will be helpful to understand the underlying models. However, it is not required to understand the control and optimization concepts.


  • From the converter to the cloud: challenges in the automation architecture of future power systems – Marco Cupelli
  • Challenges and solutions: what innovations in optimization are needed in the future electric power systems? – Gabriela Hug
  • Load management using supply function bidding – Na Li
  • Robust optimal power flow for power systems with volatile renewable generation – Ulrich Münz
  • On control concepts for microgrids – Johannes Schiffer
  • Virtual inertia emulation and placement in power grids – Florian Dörfler
  • Advanced modeling of power converters: complementarity switchings and averaged discontinuities – Francesco Vasca
  • Control challenges for modular multilevel converter (MMC) in HVDC applications – Remus Teodorescu

Click here for more information on the workshop.

Workshop 3: Simple Adaptive Control and New Results in Stability Analysis


Itzhak Barkana, BARKANA Consulting, Israel
Haim Weiss, RAFAEL, Israel
Ilan Rusnak, RAFAEL, Israel


Simple adaptive control (SAC) techniques have been conceived for large-scale systems. Before appropriate mathematical tools of analysis had been developed, SAC was considered to be just a modest version of the standard model reference adaptive control (MRAC). Further developments showed that SAC techniques can readily be applied to such applications as robots, airplanes, missiles, satellites, fine motion control, etc. Various drawbacks related to classical MRAC have been addressed and eliminated and conditions needed for robust stability have been significantly mitigated. Recent developments in nonlinear systems stability analysis tools lead to clear proofs of SAC stability in realistic environments. Realistic examples from various domains of flight control, guidance and aerospace are used to show that indeed SAC is the stable direct MRAC methodology. A non-minimum-phase and unstable UAV will be used as a detailed case-study to show the simplicity of SAC as an add-On to classical control design which improves performance. Application to real hardware will be demonstrated.

Although Lyapunov stability theory is the customary basis of any modern stability analysis, its direct application requires fitting a positive definite function to the system whose derivative ”along all trajectories of the system” is negative definite, whereas in most non-trivial problems the derivative is at most negative semi-definite. Because early extensions of Lyapunov stability theory were only covering autonomous systems, various alternatives were sought for nonautonomous systems. An alternative provided by the Barbalat Lemma imposes conditions of uniform continuity of functions and even continuity of derivatives that again could limit its applicability. Besides, even when applicable, it only ends with partial results. Although extensions of LaSalle's Invariance Principle to nonautonomous systems have been available since at least 1976, they have remained surprisingly unknown for large circles of the nonlinear control community. Moreover, even if assumed known, misinterpretations of its larger mathematical scope (that covers much more than mere asymptotic stability) may have misled users with respect to its usefulness. The review of LaSalle’s Invariance Principle along with a new extended Invariance Principle, together with a presentation of various alternatives to stability analysis, will help show the extreme efficiency of the new theorems of stability for nonlinear systems stability analysis.


  • The need for adaptation
  • Review of other adaptive control approaches.
  • Simple adaptive control for engineers
  • Optimal-control-based architectures
  • The role of passivity in adaptive (or any nonlinear) control
  • New stability results and their implications for SAC
  • Application of the SAC algorithm