Robust model predictive control through adjustable variables: an application to path planning
Abate, A.
El Ghaoui, L.
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA;
This paper appears in: Decision and Control, 2004. CDC. 43rd IEEE Conference on
Publication Date: 14-17 Dec. 2004
Volume: 3,
On page(s): 2485- 2490 Vol.3
ISSN: 0191-2216
ISBN: 0-7803-8682-5
INSPEC Accession Number: 8359993
Current Version Published: 2005-05-16
Abstract
Robustness in model predictive control (MPC) is the main focus of this work. After a definition of the conceptual framework and of the problem's setting, we analyze how a technique developed for studying robustness in convex optimization can be applied to address the problem of robustness in the MPC case. Therefore, exploiting this relationship between control and optimization, we tackle robustness issues for the first setting through methods developed in the second framework. Proofs for our results are included. As an application of this robust MPC result, we consider a path planning problem and discuss some simulations thereabout.
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
