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SUMMARY:Some methods for reducing the computational complexity of MPC
DTSTART:20140328T101500
DTSTAMP:20260408T034024Z
UID:06491b2d0a362165154de019366d8fc4305140e309aef8e644158e1d
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Daniel Axehill\nThe aim with this talk is to give an ove
 rview of some concepts related to efficient computations for MPC. The talk
  will introduce the basic concepts behind active-set solvers and how such 
 algorithms can be improved in order to reduce the number of iterations nec
 essary. Apart from decreasing the number of iterations\, it is interesting
  to reduce the computational cost for each iteration and it is outlined ho
 w a Riccati factorization can be used to reduce this cost. Beyond these st
 andard results\, it is shown how structure exploiting rank-k-updates of th
 e Riccati factorization can be performed\, how relevant search directions 
 can be computed using parallel computations\, and how problem structure st
 ill can be exploited for a condensed MPC formulation\nBio: Daniel Axehill 
 works as an assistant professor (forskarassistent) at the Division of Auto
 matic Control at the Department of Electrical Engineering at Linköping Un
 iversity. He started his graduate studies in February 2003 after completin
 g his M.Sc. degree in Applied Physics and Electrical Engineering (Y) at Li
 nköping University. Daniel received his Lic.Eng. degree in December 2005.
  The Licentiate's thesis can be found here. Daniel received his PhD degree
  in February 2008. The thesis is available from here. Daniel held a post-d
 oc position at the Automatic Control Laboratory at ETH Zurich from January
  2009 until November 2010.
LOCATION:ME C2 405 http://plan.epfl.ch/?zoom=20&recenter_y=5864084.17342&r
 ecenter_x=730960.62257&layerNodes=fonds\,batiments\,labels\,information\,p
 arkings_publics\,arrets_metro\,transports_publics&floor=2&q=me_c2%20405
STATUS:CONFIRMED
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