BEGIN:VCALENDAR
VERSION:2.0
PRODID:OpenCms ustutt.16.0.0.32
BEGIN:VTIMEZONE
TZID:Europe/Berlin
X-LIC-LOCATION:Europe/Berlin
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:19700329T020000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:19701025T030000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20230627T145434
UID:c3d44d37-14e9-11ee-832e-000e0c3db68b
SUMMARY:Vortrag von Prof. Murat Arcak
DESCRIPTION:Prof. Murat Arcak\nThe University of California, Berkeley\nBerkeley, CA, USA\n \nMonday 2023-07-03 4:00 p.m.\nIST Seminar Room 2.255 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen \nAbstract\nThe computation of reachable sets is critical for characterizing the behavior of safety-critical\nsystems. Since the reachable set can rarely be computed exactly, several methods have been\ndeveloped to approximate this set with various set representations. However, these methods\nare computationally expensive and do not scale well to high dimensional systems. This talk will\npresent a suite of methods with superior scalability properties. After a quick review of some of\nour earlier techniques using monotonicity and sensitivity concepts, we will discuss more recent\nresults with a data-driven approach. This approach is particularly suitable for\nhigh-dimensional and analytically intractable system models. We use a finite ensemble of sample\ntrajectories to compute reachable set estimates, and we provide guarantees of high accuracy\nin a probabilistic sense with associated sample complexity bounds. We will present two\ncomputational methods with this flavor. The first one uses scenario optimization to construct\nreachable set estimates as approximate solutions to chance-constrained optimization problems.\nThe second method uses a class of polynomials derived from empirical moment matrices, whose\nsublevel sets act as non-convex estimates of the reachable set. \nBiographical Information\nMurat Arcak is a professor at U.C. Berkeley in the Electrical Engineering and Computer Sciences\nDepartment, with a courtesy appointment in Mechanical Engineering. He received the B.S. degree\nin Electrical Engineering from the Bogazici University, Istanbul, Turkey (1996) and the M.S. and\nPh.D. degrees from the University of California, Santa Barbara (1997 and 2000). His research is in\ndynamical systems and control theory with applications in multi-agent systems and transportation.\nHe received a CAREER Award from the National Science Foundation in 2003, the \nDonald P. Eckman Award from\nthe American Automatic Control Council in 2006, the \nControl and Systems Theory\nPrize from the Society for Industrial and Applied Mathematics (SIAM) in 2007, and\nthe \nAntonio Ruberti\nYoung Researcher Prize from the IEEE Control Systems Society in 2014. He is a member of\nACM and SIAM, and a fellow of IEEE and the International Federation of Automatic Control\n(IFAC).\n
DTSTART;VALUE=DATE:20230703
URL;VALUE=URI:https://www.ist.uni-stuttgart.de/de/veranstaltungen/Vortrag-von-Prof.-Murat-Arcak/
END:VEVENT
END:VCALENDAR