Digital-Twins-Based Distributed Monitoring: Methodology and a Process Industry Case - a Digital Futures Distinguished lecture with Thomas Parisini
Time: Thu 2023-06-15 11.00 - 12.00
Location: U1, Brinellvägen 26, floor 3, KTH Campus
Video link: https://kth-se.zoom.us/j/69560887455
Participating: Thomas Parisini, Imperial College London & University of Trieste
Moderator: Henrik Sandberg
Administrator: Carlos Barreto Suarez, firstname.lastname@example.org
Abstract: High-fidelity digital twins represent a game-changing key enabling technology to design effective and accurate distributed monitoring systems in the absence of reliable process data under faulty scenarios.
In increasingly “smarter” large-scale applications such as critical infrastructures, manufacturing plants, etc., interconnected systems are expected to be safe, reliable, available 24/7, and of low-cost maintenance. Therefore, monitoring for faults, abnormal behaviors, cyber-attacks, etc., is of customary importance to ensure high levels of safety, performance, reliability, dependability, and availability. In the lecture, a process industry real case is considered a paradigmatic context in which faults and malfunctions can result in off-specification production, increased operating costs, production line shutdown, dangerous conditions for human operators, detrimental environmental impact, and so on. Faults, malfunctions, and cyber-attacks need to be detected promptly, and their source and severity should be diagnosed so that corrective actions can be taken as soon as possible. Once a fault is detected, the faulty subsystem can be unplugged to avoid the propagation of the fault in the interconnected large-scale system. Analogously, once the issue has been solved, the disconnected subsystem can be re-plugged in.
The distributed monitoring methodology is a model-based one in which the “model” is an accurate hardware-in-the-loop digital twin of a system to be monitored and relies on an adaptive approximation-based distributed estimation approach for large-scale systems exploiting a “divide et impera” approach in which the overall detection problem is decomposed into smaller sub-problems, which can be solved within “local” computation architectures.
Results will be shown using a digital twin of a real hot strip rolling mill located in Gallatin, TN, USA.
Bio: Thomas Parisini received the Ph.D. degree in Electronic Engineering and Computer Science in 1993 from the University of Genoa. He was with Politecnico di Milano, and he currently holds the Chair of Industrial Control and serves as the Head of the Control and Power Research Group at Imperial College London. He is a Deputy Director of the KIOS Research and Innovation Centre of Excellence, University of Cyprus. Since 2001 he is also Danieli Endowed Chair of Automation Engineering with University of Trieste. In 2009-2012 he was Deputy Rector of University of Trieste.
In 2018 he received an Honorary Doctorate from University of Aalborg, Denmark. He authored or co-authored a research monograph and over 400 research papers in archival journals, book chapters, and international conference proceedings. He is a co-recipient of the IFAC Best Application Paper Prize of the Journal of Process Control, Elsevier, for the three-year period 2011-2013 and of the 2004 Outstanding Paper Award of the IEEE Trans. on Neural Networks. He is also a recipient of the 2007 IEEE Distinguished Member Award. In 2016, he was awarded as Principal Investigator at Imperial of the H2020 European Union flagship Teaming Project KIOS Research and Innovation Centre of Excellence led by University of Cyprus with an overall budget over 40 MEuro.
Thomas Parisini has served as the 2021-2022 President of the IEEE Control Systems Society and during 2009-2016 he was the Editor-in-Chief of the IEEE Trans. on Control Systems Technology. Since 2017, he is Editor for Control Applications of Automatica and since 2018 he is the Editor in Chief of the European Journal of Control. Among other activities, he was the Program Chair of the 2008 IEEE Conference on Decision and Control and General Co-Chair of the 2013 IEEE Conference on Decision and Control. Prof. Parisini is a Fellow of the IEEE and of the IFAC.