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TECoSA Seminar – Privacy-preserving Dynamic Controllers
November 4, 2021, 15:00 – 16:00
We aim to bring you a TECoSA Seminar at kl.15 on the first Thursday of each month. This Autumn they will once again be on-line, and all are welcome to join (members accept the Outlook invite, non-members please email “firstname.lastname@example.org”). Each invited speaker will talk for about 40 minutes, followed by a panel discussion coordinated by TECoSA members.
Our third speaker this autumn is Prof Ming Cao from the Engineering and Technology Institute at the University of Groningen. Please see the abstract and short biography below. To read more about his research, please see: https://www.rug.nl/staff/m.cao/research
Panel: Lei Feng (Chair), Haydn Thompson (THHINK), Sonja Buchegger (KTH)
Privacy-preserving Dynamic Controllers
ABSTRACT: With the fast development of the Internet of Things (IoT) and cloud computing, privacy concerns of the gathering, processing and using of data have become a central research topic. As a quantitative criterion for privacy of “mechanisms” in the form of data-generating processes, the concept of differential privacy was first proposed in computer science and has later been applied to linear control systems. In fact, differential privacy can be further studied taking into account properties of dynamical systems, and then be utilized for controller design. In this talk, I first clarify that a classical concept in systems and control, input observability (sometimes referred to as left invertibility), has a strong connection with differential privacy. In particular, I show that the Gaussian mechanism can be made highly differentially private by adding small noise if the corresponding system is less input observable. Then I discuss a method to design dynamic controllers for the classic tracking control problem while addressing privacy concerns. We call the obtained controller through our design method the privacy-preserving controller. The usage of such controllers is further explained by the new insight into the trade-off between control performance and privacy level.
BIO: Since 2016, Ming Cao has been a professor of networks and robotics at the Engineering and Technology Institute (ENTEG) at the University of Groningen, the Netherlands, where he started as an assistant professor in 2008. He received the Bachelor degree in 1999 and the Master degree in 2002 from Tsinghua University, Beijing, China, and the Ph.D. degree in 2007 from Yale University, New Haven, CT, USA, all in Electrical Engineering. From September 2007 to August 2008, he was a Postdoctoral Research Associate with the Department of Mechanical and Aerospace Engineering at Princeton University, USA. He worked as a research intern during the summer of 2006 with the Mathematical Sciences Department at the IBM T. J. Watson Research Center, NY, USA.
He is the 2017 and inaugural recipient of the Manfred Thoma medal from the International Federation of Automatic Control (IFAC) and the 2016 recipient of the European Control Award sponsored by the European Control Association (EUCA). He is a Senior Editor for Systems and Control Letters, an Associate Editor for IEEE Transactions on Automatic Control, and was an associate editor for IEEE Transactions on Circuits and Systems and IEEE Circuits and Systems Magazine. He is a member of the IFAC Conference Board and a vice chair of the IFAC Technical Committee on Large-Scale Complex Systems. His research interests include autonomous agents and multi-agent systems, complex networks and decision-making processes.