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Relaxing dynamic programming

Lincoln, Bo LU and Rantzer, Anders LU (2006) In IEEE Transactions on Automatic Control 51(8). p.1249-1260
Abstract
The idea of dynamic programming is general and very simple, but the "curse of dimensionality" is often prohibitive and restricts the fields of application. This paper introduces a method to reduce the complexity by relaxing the demand for optimality. The distance from optimality is kept within prespecified bounds and the size of the bounds determines the computational complexity. Several computational examples are considered. The first is optimal switching between linear systems, with application to design of a dc/dc voltage converter. The second is optimal control of a linear system with piecewise linear cost with application to stock order control. Finally, the method is applied to a partially observable Markov decision problem (POMDP).
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
optimal control, dynamic programming, nonlinear synthesis, switching, systems
in
IEEE Transactions on Automatic Control
volume
51
issue
8
pages
1249 - 1260
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • wos:000240045500002
  • scopus:33747862706
ISSN
0018-9286
DOI
10.1109/TAC.2006.878720
language
English
LU publication?
yes
id
71c406c1-3b55-49b8-8972-88616d37cd93 (old id 395165)
date added to LUP
2007-10-08 15:15:03
date last changed
2019-08-14 02:41:23
@article{71c406c1-3b55-49b8-8972-88616d37cd93,
  abstract     = {The idea of dynamic programming is general and very simple, but the "curse of dimensionality" is often prohibitive and restricts the fields of application. This paper introduces a method to reduce the complexity by relaxing the demand for optimality. The distance from optimality is kept within prespecified bounds and the size of the bounds determines the computational complexity. Several computational examples are considered. The first is optimal switching between linear systems, with application to design of a dc/dc voltage converter. The second is optimal control of a linear system with piecewise linear cost with application to stock order control. Finally, the method is applied to a partially observable Markov decision problem (POMDP).},
  author       = {Lincoln, Bo and Rantzer, Anders},
  issn         = {0018-9286},
  keyword      = {optimal control,dynamic programming,nonlinear synthesis,switching,systems},
  language     = {eng},
  number       = {8},
  pages        = {1249--1260},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Transactions on Automatic Control},
  title        = {Relaxing dynamic programming},
  url          = {http://dx.doi.org/10.1109/TAC.2006.878720},
  volume       = {51},
  year         = {2006},
}