Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Reduced basis method and error estimation for parametrized optimal control problems with control constraints
 
research article

Reduced basis method and error estimation for parametrized optimal control problems with control constraints

Dede', Luca  
2012
Journal of Scientific Computing

We propose a Reduced Basis method for the solution of parametrized optimal control problems with control constraints for which we extend the method proposed in Dedè, L. (SIAM J. Sci. Comput. 32:997, 2010) for the unconstrained problem. The case of a linear-quadratic optimal control problem is considered with the primal equation represented by a linear parabolic partial differential equation. The standard offline–online decomposition of the Reduced Basis method is employed with the Finite Element approximation as the “truth” one for the offline step. An error estimate is derived and an heuristic indicator is proposed to evaluate the Reduced Basis error on the optimal control problem at the online step; also, the indicator is used at the offline step in a Greedy algorithm to build the Reduced Basis space. We solve numerical tests in the two-dimensional case with applications to heat conduction and environmental optimal control problems.

  • Details
  • Metrics
Type
research article
DOI
10.1007/s10915-011-9483-5
Author(s)
Dede', Luca  
Date Issued

2012

Publisher

Springer Verlag

Published in
Journal of Scientific Computing
Volume

50

Issue

2

Start page

287

End page

305

Subjects

Parametrized partial differential equations

•

Reduced Basis method

•

Optimal control

•

Control constraints

•

Error estimation

Editorial or Peer reviewed

REVIEWED

Written at

OTHER

EPFL units
MATHICSE  
Available on Infoscience
July 30, 2012
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/84325
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés