'Data-Driven Modelling in Linear Dynamic Networks' by Professor Paul M.J. Van den Hof of the Eindhoven University of Technology.
Abstract:
In many areas of science and technology, the complexity of dynamic systems that are being considered grows beyond the level of single systems into interconnected networks of dynamic systems. In control and optimisation, this has led to the development of decentralised and distributed algorithms for control/optimisation, as e.g. in multi-agent systems.
From the modelling perspective, data-driven modelling tools are typically developed for relatively simple open-loop and closed-loop structures, while the opportunities for big data handling in the current data science era are becoming abundant. As a result, there is a strong need for the development of data-driven modelling tools for large-scale interconnected dynamic networks.
In this seminar, we will highlight the main developments and challenges in this area. Besides setting up a modelling framework, we will address problems of local identification of a particular part of the network, including the selection of the appropriate signals to be measured. The concept of network identifiability is highlighted and the role of structural properties of the network, in terms of its topology/graph, is given strong attention. It is also shown how classical closed-loop identification methods need to be generalised to be able to cope with new situations.
Biography:
Paul M. J. Van den Hof received the MSc and PhD degrees in electrical engineering from Eindhoven University of Technology, Eindhoven, The Netherlands, in 1982 and 1989, respectively. In 1986 he moved to Delft University of Technology, where he was appointed as Full Professor in 1999. From 2003 to 2011, he was founding co-director of the Delft Center for Systems and Control (DCSC). From 2005-2015 he was scientific director of the Dutch Institute for Systems and Control (DISC).
As of 2011, he is a Full Professor and heading the control systems group in the Electrical Engineering Department of Eindhoven University of Technology. His research interests include system identification, identification for control, and model-based control and optimization, with applications in industrial process control systems, including petroleum reservoir engineering systems, and high-tech systems. He holds an ERC Advanced Research grant for a research project on identification in dynamic networks.
Paul Van den Hof is an IFAC Fellow and IEEE Fellow, and Honorary Member of the Hungarian Academy of Sciences. He has been a member of the IFAC Council (1999–2005, 2017-2020), the Board of Governors of IEEE Control Systems Society (2003–2005), and an Associate Editor and Editor of Automatica (1992–2005). In the triennium 2017-2020, he serves as chair of the Executive Board and Vice-President of IFAC.