Execution time certification for gradient-based optimization in model predictive control
Giselsson, Pontus LU
(2012)
51st IEEE Conference on Decision and Control, 2012
p.3165-3170
- Abstract
- We consider model predictive control (MPC) problems with linear dynamics, polytopic constraints, and quadratic objective. The resulting optimization problem is solved by applying an accelerated gradient method to the dual problem. The focus of this paper is to provide bounds on the number of iterations needed in the algorithm to guarantee a prespecified accuracy of the dual function value and the primal variables as well as guaranteeing a prespecified maximal constraint violation. The provided numerical example shows that the iteration bounds are tight enough to be useful in an inverted pendulum application.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2278041
- author
- Giselsson, Pontus
LU
- organization
- publishing date
- 2012
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- [Host publication title missing]
- pages
- 3165 - 3170
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 51st IEEE Conference on Decision and Control, 2012
- conference location
- Maui, Hawaii, United States
- conference dates
- 2012-12-10 - 2012-12-13
- external identifiers
-
- wos:000327200403085
- scopus:84874236767
- ISSN
- 0191-2216
- project
- LCCC
- language
- English
- LU publication?
- yes
- additional info
- key=gis_cert_2012cdc
- id
- 7d03cc66-1185-4c76-b3ad-30f7fe7cd54d (old id 2278041)
- date added to LUP
- 2016-04-01 15:05:22
- date last changed
- 2024-01-25 10:19:15
@inproceedings{7d03cc66-1185-4c76-b3ad-30f7fe7cd54d,
abstract = {{We consider model predictive control (MPC) problems with linear dynamics, polytopic constraints, and quadratic objective. The resulting optimization problem is solved by applying an accelerated gradient method to the dual problem. The focus of this paper is to provide bounds on the number of iterations needed in the algorithm to guarantee a prespecified accuracy of the dual function value and the primal variables as well as guaranteeing a prespecified maximal constraint violation. The provided numerical example shows that the iteration bounds are tight enough to be useful in an inverted pendulum application.}},
author = {{Giselsson, Pontus}},
booktitle = {{[Host publication title missing]}},
issn = {{0191-2216}},
language = {{eng}},
pages = {{3165--3170}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Execution time certification for gradient-based optimization in model predictive control}},
url = {{https://lup.lub.lu.se/search/files/4331663/3131657.pdf}},
year = {{2012}},
}