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SUMMARY:A Set Membership approach to the identification of linear systems 
 with guaranteed simulation accuracy.
DTSTART:20190124T111500
DTEND:20190124T121500
DTSTAMP:20260928T192438Z
UID:19b2c6399385dead6fd2f5430d94622afc8ca0d728c63f0c3afc1f1f
CATEGORIES:Conferences - Seminars
DESCRIPTION:Marco Lauricella\, Politecnico di Milano\nAbstract: The identi
 fication of models of linear systems having guaranteed simulation accuracy
  is of great importance in all the cases where a model and a measure of it
 s uncertainty are needed for long range prediction or simulation purpose\,
  like in robust Model Predictive Control. In this talk\, I will address th
 e problem of model identification for linear systems affected by a bounded
  additive disturbance\, where the bound is unknown\, and a finite set of s
 ampled data is available for model identification. The objective is the id
 entification of one-step-ahead models\, and the estimation of their accura
 cy by means of worst-case simulation error bounds\, resorting to the Set M
 embership identification framework. I will present new results that allow 
 to develop a procedure for the estimation of the unknown disturbance bound
  and of the system decay rate from data. Then\, the available data and the
  estimated disturbance bound are used to define the set of all the possibl
 e models that are compatible with data and with the estimated quantities. 
 The estimated decay rate is used to refine the standard Feasible Parameter
  Set (FPS) formulation\, by adding constraints that enforce a converging b
 ehavior of the iterated models. Finally\, the desired one-step-ahead model
  is identified by numerical optimization\, and the worst-case error bound 
 related to the obtained model is calculated over the available data and FP
 Ss. The performance and the validity of the proposed approach are evaluate
 d over numerical simulations and a real world experimental case study.\n\n
 Bio: Marco Lauricella received the B.Sc. and M.Sc. degrees in Automation 
 and Control Engineering from Politecnico di Milano\, Italy\, in 2013 and 2
 015\, respectively. He is currently a PhD Fellow in Information Engineerin
 g at the Department of Electronic\, Information and Bio-engineering of Pol
 itecnico di Milano\, Italy. His research interests include system identifi
 cation and fault detection\, and their applications to electric systems.
LOCATION:ME C2 405 https://plan.epfl.ch/?room=MEC2405
STATUS:CONFIRMED
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