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SUMMARY:Observability\, Identification and Lie Symmetries in Structural He
 alth Monitoring Problems - Prof Manolis Chatzis\, Oxford University 
DTSTART:20241108T160000Z
DTEND:20241108T170000Z
UID:TALK219805@talks.cam.ac.uk
CONTACT:46601
DESCRIPTION:Non-linear dynamic systems arise naturally in several applicat
 ions either due to the underlying constitutive laws and geometric non-liea
 rities\, or simply because of how a researcher approaches a problem.\n\nA 
 special category of non-linear systems is that of non-smooth dynamics syst
 ems\, i.e.\, systems whose equations of motion\, or measurement equation\,
  include terms that are not infinitely differentiable with respect to some
  of their states. Such systems often arise in engineering and are often re
 lated to some form of damage\, e.g.\, sliding\, impact\, hysteresis or fra
 cture.\n\nThe accurate modeling of non-smooth systems becomes an important
  task because of the connection of such behaviors to failure and the incre
 ased inherent uncertainty. An added challenge to Structural Health Monitor
 ing applications is that the excitations to systems representing infrastru
 cture elements are often impossible to measure\, e.g.\, as in the case of 
 the wind excitations to bridges and wind turbines.\n\nAn important means t
 o tackle the previous challenges and reduce the effects of other sources o
 f uncertsainty is through system identification\, i.e.\, estimating the be
 havior and properties of the system using data obtained from sensors.\n\nP
 rior to using an algorithm for identifying the system it is worth to inves
 tigate if this would be possible even under ideal conditions\, i.e. invest
 igating the theoretical observability and identifiability of the system. I
 n situations where the system is not observable for an examined sensor set
 up\, it is also interesting to investigate what are the equivalent transfo
 rmations of the dynamic states that one may be tracking\, i.e. the Lie Sym
 metries of the system. In doing so\, the non-smooth nature of a system\, t
 he high-dimensionality of the models corresponding to real-life applicatio
 ns\, and the common reality of not measuring all of the inputs pose challe
 nges.\n\nIn this seminar\, developments on the Observability\, Lie Symmetr
 ies and Identification of non-linear systems is discussed. Improvements on
  Observability algorithms to handle large linear- and non-linear systems a
 nd unknown inputs are presented. Motivating examples from structural syste
 ms including bridges and offshore wind turbines are provided.\n\n\nShort B
 io: Manolis Chatzis is an Associate Professor in the Department of Enginee
 ring Science at the University of Oxford and a Tutorial Fellow for Hertfor
 d College. Prior to joining Oxford in 2013 Manolis was a Post-Doctoral Res
 earch Scientist at Columbia University in the City of New York. He holds a
  Diploma in Civil Engineering and an MSc. in Structural Engineering from t
 he National Technical University of Athens. He was awarded a PhD from Colu
 mbia University in the City of New York in 2012. His research focuses on t
 he study of non-linear dynamic systems with emphasis in developing algorit
 hms for their modeling and identification.
LOCATION:JDB Seminar Room\, CUED
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