Convex Dynamic Programming for Hybrid Systems
(2002) In IEEE Transactions on Automatic Control 47(9). p.1536-1540- Abstract
- A classical linear programming approach to optimization of flow or transportation in a discrete graph is extended to hybrid systems. The problem is finite-dimensional if the state space is discrete and finite, but becomes infinite-dimensional for a continuous or hybrid state space. It is shown how strict lower bounds on the optimal loss function can be computed by gridding the continuous state space and restricting the linear program to a finite-dimensional subspace. Upper bounds can be obtained by evaluation of the corresponding control laws.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/162021
- author
- Hedlund, Sven LU and Rantzer, Anders LU
- organization
- publishing date
- 2002
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- hybrid systems, Terms—Convex optimization, dynamic programming, optimal control, linear program
- in
- IEEE Transactions on Automatic Control
- volume
- 47
- issue
- 9
- pages
- 1536 - 1540
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- wos:000177921900017
- scopus:0036740941
- ISSN
- 0018-9286
- DOI
- 10.1109/TAC.2002.802753
- language
- English
- LU publication?
- yes
- id
- 8ea9573b-5cd4-47cc-b4ed-5fc27ee78f02 (old id 162021)
- date added to LUP
- 2016-04-01 16:20:14
- date last changed
- 2023-09-04 16:52:24
@article{8ea9573b-5cd4-47cc-b4ed-5fc27ee78f02, abstract = {{A classical linear programming approach to optimization of flow or transportation in a discrete graph is extended to hybrid systems. The problem is finite-dimensional if the state space is discrete and finite, but becomes infinite-dimensional for a continuous or hybrid state space. It is shown how strict lower bounds on the optimal loss function can be computed by gridding the continuous state space and restricting the linear program to a finite-dimensional subspace. Upper bounds can be obtained by evaluation of the corresponding control laws.}}, author = {{Hedlund, Sven and Rantzer, Anders}}, issn = {{0018-9286}}, keywords = {{hybrid systems; Terms—Convex optimization; dynamic programming; optimal control; linear program}}, language = {{eng}}, number = {{9}}, pages = {{1536--1540}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Transactions on Automatic Control}}, title = {{Convex Dynamic Programming for Hybrid Systems}}, url = {{https://lup.lub.lu.se/search/files/4641862/625670.pdf}}, doi = {{10.1109/TAC.2002.802753}}, volume = {{47}}, year = {{2002}}, }