Paper Info
Title
A Proximity Moving Horizon Estimator Based On Bregman Distances And Relaxed Barrier Functions
Abstract
In this paper, we introduce a general proximity-based formulation for moving horizon estimation (MHE) of constrained discrete-time linear systems. The cost function of the underlying optimization problem consists of convex stage costs as well as Bregman distances centered around the a priori estimates. The Bregman term allows to incorporate constraints into the cost function by means of relaxed barrier functions and to formulate the moving horizon estimator as an unconstrained optimization problem. The stability properties of the proposed estimator are investigated and the obtained results are illustrated by means of a numerical example.
Year
DOI
Venue
2019
10.23919/ECC.2019.8795714
2019 18TH EUROPEAN CONTROL CONFERENCE (ECC)
Field
DocType
Citations 
Mathematical optimization,Linear system,Computer science,A priori and a posteriori,Horizon,Regular polygon,Moving horizon estimation,Optimization problem,Estimator
Conference
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Meriem Gharbi101.01
Christian Ebenbauer220030.31