A structure exploiting interior-point method for moving horizon estimation

Author

Haverbeke, Niels ; Diehl, Moritz ; De Moor, Bart

Author_Institution

Dept. of Electr. Eng., Katholieke Univ. Leuven, Heverlee, Belgium

fYear

2009

fDate

15-18 Dec. 2009

Firstpage

1273

Lastpage

1278

Abstract

In this article a primal barrier interior-point method for moving horizon estimation (MHE) is presented. It exploits the structure of the KKT systems yielding an algorithm with linear complexity in the horizon length as opposed to cubically as in unstructured solvers. Ideas of square root covariance Kalman filtering are proposed in order to update covariance matrices occurring in the factorization of the KKT matrix efficiently and in a numerically stable way. The algorithm is able to compute - without any additional costs - the covariance of the last estimate within the horizon, which reflects the accuracy of the estimate.

Keywords

Kalman filters; Riccati equations; covariance matrices; optimisation; state estimation; KKT matrix; KKT system; Riccati equation; covariance matrix; horizon length; interior-point method; linear complexity; moving horizon estimation; optimization; square root covariance Kalman filtering; Costs; Covariance matrix; Filtering; Kalman filters; Optimal control; Predictive control; Predictive models; Riccati equations; Stability; State estimation; Matrix Riccati equations; Optimal filtering; Optimization problems; State estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Conference_Location

Shanghai

ISSN

0191-2216

Print_ISBN

978-1-4244-3871-6

Electronic_ISBN

0191-2216

Type

conf

DOI

10.1109/CDC.2009.5400804

Filename

5400804