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CATEGORIES:CUED Control Group Seminars
SUMMARY:Data-driven control of hybrid systems and Chance-C
 onstrained optimization - Raphael Jungers\, UC Lou
 vain
DTSTART;TZID=Europe/London:20230214T140000
DTEND;TZID=Europe/London:20230214T150000
UID:TALK197233AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/197233
DESCRIPTION:Control systems are increasingly complex\, often a
 t the point that obtaining a model for them is out
  of reach. In some situations\, (parts of) the sys
 tems are proprietary\, so that the very equations 
 that rule their behaviour cannot be known. On the 
 other hand\, the ever-growing progress in hardware
  technologies often enables one to retrieve massiv
 e data\, e.g. from embedded sensors. Because of th
 ese evolutions\, control theory is moving from a m
 odel-based towards a model-free and data-driven pa
 radigm.\n\nFor Linear Time-invariant systems\, cla
 ssical results from Identification theory provide 
 a rather straightforward approach. However\, these
  approaches become useless (or at least inefficien
 t) if one relaxes the strong assumptions they rely
  upon (linearity\, gaussian noise\, etc.). This is
  especially the case in safety-critical applicatio
 ns\, where one needs guarantees on the performance
  of the obtained solution.\n\nDespite these diffic
 ulties\, one may sometimes recover firm guarantees
  on the behaviour of the system. This may require 
 to change one’s point of view on the nature of the
  guarantees we ask.  I will provide examples of su
 ch results for different control tasks and differe
 nt complex systems\, and will raise the question o
 f theoretical fundamental barriers for these probl
 ems.\n\nThe seminar will be held in the Control La
 b BN4-85\, Department of Engineering\, and online 
 (zoom): https://us06web.zoom.us/j/87986687566?pwd=
 MGJScmMwd2lwT0tVMHNmWmxSa05XZz09
LOCATION:Department of Engineering / Online (Zoom)
CONTACT:Fulvio Forni
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