Multi-Input Multi-Output Ellipsoidal State Bounding

C. Durieu, É. Walter and B. Polyak
Additional contact information
C. Durieu: Centre National de la Recherche Scientifique and École Normale Supérieure de Cachan
É. Walter: École Supérieure d'Électricité, and Université de Paris-Sud
B. Polyak: Russian Academy of Sciences

Journal of Optimization Theory and Applications, 2001, vol. 111, issue 2, No 3, 273-303

Abstract: Abstract Ellipsoidal state outer bounding has been considered in the literature since the late sixties. As in the Kalman filtering, two basic steps are alternated: a prediction phase, based on the approximation of the sum of ellipsoids, and a correction phase, involving the approximation of the intersection of ellipsoids. The present paper considers the general case where K ellipsoids are involved at each step. Two measures of the size of an ellipsoid are employed to characterize uncertainty, namely, its volume and the sum of the squares of its semiaxes. In the case of multi-input multi-output state bounding, the algorithms presented lead to less pessimistic ellipsoids than the usual approaches incorporating ellipsoids one by one.

Keywords: Bounded noise; ellipsoidal bounding; identification; set-membership estimation; state estimation (search for similar items in EconPapers)
Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://link.springer.com/10.1023/A:1011978200643 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:111:y:2001:i:2:d:10.1023_a:1011978200643

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1023/A:1011978200643

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().