The European Control Conference offers pre-conference workshops addressing current and future topics in control systems from experts in academia, research institutes, and industry. Pre-conference workshops cover material or use presentation formats that are not found within the main conference to increase the interest for the event, enhance interaction and discussion amongst participants, and make useful connections to fields outside of control.

Main conference registration is a prerequisite for registering at ECC workshops.

Important: please note that you can register for only one workshop, since all workshops take place simultaneously. Recordings of workshops will not normally be made.

Information about the costs of attending a pre-conference workshop and how to register is available on the conference registration page.

The list of confirmed workshops is reported below. For further information contact the conference Workshops Chair, prof. Maria Elena Valcher.

ECC23 is hosting the following four confirmed workshops, on Tuesday, June 13th 2023 (full day):

1. Formal methods for data-driven control systems.
2. Concurrent Learning and Optimization for Nonconvex Constrained Problems – A Set Membership approach.
3. Guidance, navigation and control strategies for small-scale robotic platforms.
4. Consensus and Synchronization of Autonomous Agents on Lie Groups.( Cancelled )

Formal methods for data-driven control systems

Date & Time:

Tuesday, June 13th 2023 @ 9:00 -17:00 (TBC)

Location:

Library. Room: L.2.2
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Organizers:

Antoine Girard
Raphael Jungers
Manuel Mazo

Abstract:

Symbolic control and formal methods have been a promising direction in Systems and Control for several decades. Indeed, they allow in principle to provide formal guarantees on the behaviour of dynamical systems, even very complicated ones, by analysing models of such systems. However, such complicated systems are often naturally studied in a ‘model-free’, ‘data-driven’ fashion. Think for instance of a self-driving car, with many heterogeneous and complex components: this system is hard to model rigorously, but at the same time generates a huge amount of data via its many embedded sensors. Other examples include complex robots, smart grids, and many other modern systems. If data are certainly an opportunity for symbolic control of complex systems, they provide technical challenges that are not well understood nowadays: how can one reconcile the intrinsically random nature of data-driven approaches with certified guarantees? How can we certify asymptotic properties from finite-time observations? In recent years, these questions have found partial answers and deep relations with topics such as Interval Markov Chains, the Scenario Approach, Ergodic Dynamics or Monotone Systems. The event will consist of seven 40-minutes presentations from various leading researchers active in the topic. The goal of this full-day workshop is to introduce this recently emerged challenge to the community. As such, the talks will be aimed at a general public in control, with an emphasis on pedagogy to provide an entrance point to this exciting field in our community. The day will end with a panel discussion on the future directions of the topic.

Program:

The detailed program of this workshop is available here.

Concurrent Learning and Optimization for Nonconvex Constrained Problems – A Set Membership approach

Date & Time:

Tuesday, June 13th 2023 @ 9:00 – 17:30

Location:

Library. Room: L.2.1
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Organizers:

Lorenzo Fagiano
Fredy Ruiz
Lorenzo Jr. Sabug

Abstract:

When seeking the global minimum of a general non-convex problem, any sensible approach must concurrently learn, to gather knowledge about the cost and constraints, and optimize, to find better and better values of the decision variables inside the feasible region. When the cost and constraint functions are not available analytically, these two tasks must be carried out using only data samples – hence the name “black-box optimization”. Black-box optimization is highly relevant to many science and engineering fields. Examples are system design optimization using detailed simulations, system/control tuning via experiments, control adaptation, parameter identification for nonlinear models, training of neural networks and other nonlinear approximators, experiment design. This workshop will provide an overview of the main solution approaches in the literature, then introduce a new methodology and the related algorithm, named SMGO – Set Membership Global Optimization. Thanks to an interactive, hands-on session, the participants will be able to immediately test SMGO and compare it with other approaches. A final session and discussion will highlight challenges and promising research directions.

Program:

The detailed program of this workshop is available here.

Guidance, navigation and control strategies for small-scale robotic platforms

Date & Time:

Tuesday, June 13th 2023 @ 9:30 -17:30

Location:

Library. Room: L.2.3
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Organizers:

Florin Stoican
Sylvain Betrand
Ionela Prodan

Abstract:

Small scale robotic platforms are fast becoming ubiquitous. We expect that the next decade will show an exponential growth in various applications. Among the many challenges, we may mention the unstructured environment and human interactions and the relatively low cost (and thus low performance) sensing modules available. All these limitations impose a rethinking of standard  motion planning algorithms to emphasize redundancy, reliability and quick validation for unexpected mission changes. Consequently, both beginners and experts have to become accustomed with new results and tools at an increasingly hectic pace. We propose in this workshop to: i) cover new results from guidance, control and estimation for single and multi-agent systems; and ii) to validate them via simulation and experiments in interactive sessions.  Our approach, proposed for this workshop, is to provide a complete (but obviously not exhaustive) implementation stack for the control of a set of small scale indoor robotic platforms (ground-based or aerial):

•  provide a model-based guidance mechanism which, via flatness descriptions and subsequent spline parametrizations, gives a feasible path;
•  propose various control strategies (linear, feedback linearizable, receding horizon control) to track the path;
•  discuss and compare centralized versus distributed control implementations;
•   present and solve estimation and formation control issues (for realistic mission requirements).

We consider the usual sources of difficulty: control saturation and path feasibility; obstacle and collision avoidance conditions; task assignment and formation control. We seek Master/PhD candidates and early-career researchers who wish to understand all the necessary steps (guidance, control and navigation) required in handling robotic platforms in small spaces (where internal dynamics are especially relevant and where GPS-like positioning systems are not always available). The tools that we provide may be of use not only for researchers whose main activity is in robotics but also for those, eg. from the control community, who want to test their theoretical results on systems inspired from real applications. The workshop requires a basic knowledge in the principles of constrained optimization, linear and nonlinear control (state-based), receding horizon framework. Familiarity with Matlab/Python as scripting languages, Gazebo (or similar) as simulation platform, and/or ROS as middleware for robotics, is welcomed.  A strong point of our workshop proposal is the availability of a hardware platform which may be used by the participants for experimental validation. The lab is 500m from the conference venue, in the UPB campus. In fact, depending on the participant number, the ancillary equipment may be moved to the conference premises with ease.

Program:

The detailed program of this workshop is available here.