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SUMMARY:On the approximation of constrained infinite-horizon linear quadra
 tic regulator problems
DTSTART:20170629T101500
DTEND:20170629T111500
DTSTAMP:20260919T215532Z
UID:6cc71617ef3966b6ef885675e37255a0429ce82a6a22e81804a6b8d3
CATEGORIES:Conferences - Seminars
DESCRIPTION:Michael Mühlebach\, Institute for Dynamic Systems and Contro
 l\, ETH\nAbstract: I will construct approximations to constrained infinite
 -horizon linear quadratic optimal control problems arising in model predic
 tive control.\nInput and state trajectories will be parameterized as a lin
 ear combination of basis functions and the dynamics are approximated by a 
 Galerkin\napproach. I will argue that the resulting optimization problems 
 lead to inherent closed-loop stability and recursive feasibility\nwhen app
 lied in the context of model predictive control. Moreover\, I will derive 
 a bound on the suboptimality of the approximation and present\nsimulation 
 results indicating that the underlying infinite-dimensional optimal contro
 l problem is well-approximated. In addition\, I will show\nexperimental re
 sults to confirm that the approach works in practice.\n\nBio: Michael Müh
 lebach received the Bachelor and Master degrees from ETH Zurich in 2010 an
 d 2013\, respectively. He received the Outstanding D-MAVT Bachelor Award f
 or his Bachelor studies and the Willi-Studer prize for the best Master deg
 ree in Robotics\, Systems\, and Control. He did his master thesis on varia
 tional integrators for Hamiltonian systems and their application to multib
 ody dynamics. His main research interests include multibody dynamics\, the
  control of nonlinear systems\, and model predictive control.
LOCATION:ME C2 405 https://plan.epfl.ch/theme/generalite_thm_plan_public?r
 equest_locale=en&room=ME%20C2%20405&domain=places&dim_floor=2&lang=en&dim_
 lang=en&baselayer_ref=grp_backgrounds&tree_groups=centres_nevralgiques%
STATUS:CONFIRMED
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