Fault detection in large scale nonlinear systems: an optimization-based approach with probabilistic performance
Event details
| Date | 22.05.2015 |
| Hour | 10:15 |
| Speaker | Peyman Mohajerin Esfahani |
| Location | |
| Category | Conferences - Seminars |
In this seminar we present a novel perspective along with a scalable methodology to design a fault detection and isolation (FDI) filter for high dimensional nonlinear systems. Previous approaches on FDI problems are either confined to linear systems or they are only applicable to low dimensional dynamics with specific structures. In contrast, shifting attention from the system dynamics to the disturbance inputs, we propose a relaxed design perspective to train a linear residual generator given some statistical information about the disturbance patterns. We then propose an optimization-based approach to robustify the filter with respect to finitely many signatures of the nonlinearity. Invoking recent results in randomized optimization, we also provide theoretical guarantees for the performance of the proposed filer. The discussion will be motivated by a cyber-physical attack emanating from the vulnerabilities introduced by the interaction between IT infrastructure and power system
Bio:
Peyman Mohajerin Esfahani holds a dual-appointment as a postdoctoral researcher at the Risk Analytics and Optimization Chair at EPFL and the Automatic Control Laboratory at ETH Zurich since April 2014. He is currently a visiting research scholar at the Laboratory for Information and Decision Systems at MIT. He received the B.Sc. and M.Sc degrees in Electrical Engineering both from Sharif University of Technology, Tehran, Iran, in September 2005 and December 2007, respectively. In June 2008 he joined the Automatic Control Laboratory at ETH Zurich, where he obtained the Ph.D. degree in January 2014. His research interests include theoretical and practical aspects of decision making problems in uncertain and dynamic environments subject to information constraints, with applications to control and security of large-scale and distributed systems, in particular power networks and industrial cyber-physical systems.
Bio:
Peyman Mohajerin Esfahani holds a dual-appointment as a postdoctoral researcher at the Risk Analytics and Optimization Chair at EPFL and the Automatic Control Laboratory at ETH Zurich since April 2014. He is currently a visiting research scholar at the Laboratory for Information and Decision Systems at MIT. He received the B.Sc. and M.Sc degrees in Electrical Engineering both from Sharif University of Technology, Tehran, Iran, in September 2005 and December 2007, respectively. In June 2008 he joined the Automatic Control Laboratory at ETH Zurich, where he obtained the Ph.D. degree in January 2014. His research interests include theoretical and practical aspects of decision making problems in uncertain and dynamic environments subject to information constraints, with applications to control and security of large-scale and distributed systems, in particular power networks and industrial cyber-physical systems.
Practical information
- Expert
- Free