On Approximate Dynamic Programming in Switching Systems
(2005) 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 p.1391-1396- Abstract
- In order to simplify computational methods based on dynamic programming, an approximative procedure based on upper and lower bounds of the optimal cost was recently introduced. The convergence properties of this procedure are analyzed in this paper. In particular, it is shown that the computational effort in finding an approximately optimal control law by relaxed value iteration is related to the polynomial degree that is needed to approximate the optimal cost. This gives a rigorous foundation for the claim that the search for optimal control laws requires complex computations only if the optimal cost function is complex. A computational example is given for switching control on a graph with 60 nodes, 120 edges and 30 continuous states.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/535807
- author
- Rantzer, Anders LU
- organization
- publishing date
- 2005
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proceedings of the 44th IEEE Conference on Decision and Control and the 2005 European Control Conference
- pages
- 1391 - 1396
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05
- conference location
- Seville, Spain
- conference dates
- 2005-12-12 - 2005-12-15
- external identifiers
-
- wos:000240653701064
- scopus:33847215503
- ISBN
- 0-7803-9568-9
- DOI
- 10.1109/CDC.2005.1582353
- language
- English
- LU publication?
- yes
- id
- 22426452-1154-4a1f-9d2b-3996beb4d9c4 (old id 535807)
- date added to LUP
- 2016-04-04 12:06:34
- date last changed
- 2023-09-20 13:43:16
@inproceedings{22426452-1154-4a1f-9d2b-3996beb4d9c4, abstract = {{In order to simplify computational methods based on dynamic programming, an approximative procedure based on upper and lower bounds of the optimal cost was recently introduced. The convergence properties of this procedure are analyzed in this paper. In particular, it is shown that the computational effort in finding an approximately optimal control law by relaxed value iteration is related to the polynomial degree that is needed to approximate the optimal cost. This gives a rigorous foundation for the claim that the search for optimal control laws requires complex computations only if the optimal cost function is complex. A computational example is given for switching control on a graph with 60 nodes, 120 edges and 30 continuous states.}}, author = {{Rantzer, Anders}}, booktitle = {{Proceedings of the 44th IEEE Conference on Decision and Control and the 2005 European Control Conference}}, isbn = {{0-7803-9568-9}}, language = {{eng}}, pages = {{1391--1396}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{On Approximate Dynamic Programming in Switching Systems}}, url = {{https://lup.lub.lu.se/search/files/5929427/625586.pdf}}, doi = {{10.1109/CDC.2005.1582353}}, year = {{2005}}, }