Plenary Lectures

  • Cyberphysical Security of Critical Infrastructures - Prof. Vicenç PUIG
    Universitat Politècnica de Catalunya · BarcelonaTech (UPC) - Spain

    The secure operation of critical infrastructures is a growing concern with the advent of cyberphysical systems paradigm that leads to the interconnection of the digital and physical worlds. The increase of system connectivity with the the use of new communication facilities have an important number of potential benefits. However, new problems that before were not considered as the increasing vulnerability to attacks as confirmed by the rise of cybersecurity incidents in several critical infrastructures worldwide. This fact has recently motivated in the research community a growing interested in developing methods for the detecting attacks in cyberphysical systems and their reconfiguration to preserve the secure operation.

    This talk will introduce the problem of cyberphysical security and some possible approaches in the context of critical infrastructures. This type of cyberphysical systems has specific particularities as the networked structure, the large size and complexity of already deployed automatic control systems. For illustrating the proposed approaches, real case studies based on water networks will used along the presentation. The talk will end presenting some discussion about possible future developments and about the cooperation between the FDI and cybersecurity communities

  • Dealing with uncertainty in learning-based control and optimization: the Set membership paradigm
    Dr. Lorenzo FAGIANO - Politecnico di Milano · Milan - Italy

    Most engineering problems can be cast as follows: given prior information and data (models, requirements, experimental data, etc.), estimate or "learn" a vector of parameters (model parameters, system design parameters, controller parameters, etc.) that are optimal according to a suitably defined criterion. The most common approaches to deal with this problem return one parameter vector ("model first"). Quantifying the related uncertainty or robustness is often challenging : yet, in safety-critical applications the uncertainty associated with a solution can be more important than the solution itself. Set Membership methods are a family of approaches designed to compute an uncertainty estimate ("uncertainty first") in the form of a set of admissible parameters, rather than returning a single point. Thus, they provide a systematic way to associate uncertainty to a given parameter vector and to choose, for example, the parameters that minimize uncertainty. The talk will briefly review the main concepts of Set Membership methods and focus on two specific techniques: the design of adaptive model predictive controllers and the global, derivative-free solution of black-box optimization problems, where both the cost and the constraint functions are not tractable analytically.

  • Damage compensation in robotics without diagnosis - Dr. Jean-Baptiste MOURET
    INRIA · Nancy - France

    Robots are complex and fragile machine that easily stop working in difficult conditions. To be deployed outside of labs and the manufacturing industry, they need to cope with unexpected damage. During the last 6 years, we developped a family of algorithms that exploit data-efficient trial-and-error learning (reinforcement learning) to find compensatory behaviors without any explicit diagnosis. For instance, they allow a 6-legged robot with a broken leg to discover new gaits in less than 2 minutes (a dozen of trials), or a humanoid robot to avoid failing when a motor in the leg is disconnected.

     

Prof. Vicenç Puig received the telecommunications engineering degree in 1993 and the Ph.D. degree in Automatic Control, Vision, and Robotics in 1999, both from Universitat Politècnica de Catalunya (UPC). He is Full Professor of the Automatic Control Department and a Researcher at the Institut de Robòtica i Informàtica Industrial, both from the UPC. He is currently the Director of the Automatic Control Department and Head of the Research Group in Advanced Control Systems at UPC. He has developed important scientific contributions in the areas of fault diagnosis and fault tolerant control using interval and linear-parameter-varying models using set-based approaches. He has participated/leaded more than 20 European and national research projects in the last decade. He has also led many private contracts with several companies and has published more than 120 journal articles and more than 450 in international conference/ workshop proceedings. He has supervised over 20 Ph.D. dissertations and over 40 master’s theses/final projects. He is currently the chair of the IFAC Safeprocess TC Committee 6.4 (2020-until now) and was the  vice chair (2014–2017). He has been the general chair of the Third IEEE Conference on Control and Fault-Tolerant Systems (Systol 2016 and 2021) and the IPC chair of the IFAC Safeprocess 2018.
 photo Lorenzo Fagiano

 

Dr. Lorenzo Fagiano received the Ph.D. degree in Information and Systems Engineering in 2009 from Politecnico di Torino, Italy. From 2010 to 2013 he held positions as Marie Curie Fellow at UC Santa Barbara, and ETH Zurich. From 2013 to 2016 he was scientist and senior scientist at ABB Switzerland, Corporate Research. He is currently associate professor of automation and control engineering at the Politecnico di Milano, Italy. His research interests include constrained estimation and control, set membership methods, and applications to industrial, robotic and energy systems. He served as associate editor of the IEEE Transactions of Control Systems Technology in the period 2015-2020. He is recipient of the 2019 European Control Award, of the Mission Innovation Champion award 2019 for Italy, of two Marie Curie individual fellowships (2009 and 2012), of the 2011 IEEE Transactions on Control Systems Technology Outstanding Paper Award, and of the 2010 ENI award ‘‘Debut in Research’’ prize.
   

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