Exact recursive updating of state uncertainty sets for linear SISO systems

Hill, R, Luo, Y and Schwerdtfeger, U 2018, 'Exact recursive updating of state uncertainty sets for linear SISO systems', Automatica, vol. 95, pp. 33-43.


Document type: Journal Article
Collection: Journal Articles

Title Exact recursive updating of state uncertainty sets for linear SISO systems
Author(s) Hill, R
Luo, Y
Schwerdtfeger, U
Year 2018
Journal name Automatica
Volume number 95
Start page 33
End page 43
Total pages 11
Publisher Elsevier
Abstract This paper addresses the classical problem of determining the set of possible states of a linear discrete-time SISO system subject to bounded disturbances, from measurements corrupted by bounded noise. These so-called uncertainty sets evolve with time as new measurements become available. We present two theorems which give a complete description of the relationship between uncertainty sets at two successive time instants, and this yields an efficient algorithm for recursively updating uncertainty sets. Numerical simulations demonstrate performance improvements over existing exact methods.
Subject Engineering not elsewhere classified
Mathematical Sciences not elsewhere classified
Information and Computing Sciences not elsewhere classified
Keyword(s) Duality
Estimation
Linear programming
Linear systems
Uncertainty
DOI - identifier 10.1016/j.automatica.2018.05.010
Copyright notice © 2018 Elsevier Ltd. All rights reserved.
ISSN 0005-1098
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 0 times in Scopus Article
Altmetric details:
Access Statistics: 4 Abstract Views  -  Detailed Statistics
Created: Tue, 26 Mar 2019, 09:36:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us