Details
Original language | English |
---|---|
Pages (from-to) | 306-314 |
Number of pages | 9 |
Journal | Automatica |
Volume | 79 |
Early online date | 6 Mar 2017 |
Publication status | Published - 1 May 2017 |
Externally published | Yes |
Abstract
In this paper, we propose a new moving horizon estimator for nonlinear detectable systems. Similar to a recently proposed full information estimator, the corresponding cost function contains an additional max-term compared to more standard least-squares type approaches. We show that robust global asymptotic stability in case of bounded disturbances and convergence of the estimation error in case of vanishing disturbances can be established. Second, we show that the same results hold for a standard least-squares type moving horizon estimator, which so far has not been proven even in the full information estimation case. An additional advantage of the proposed estimators is that a suitable prior weighting appearing in the cost function can explicitly be determined offline, which is not the case in various existing approaches.
Keywords
- Moving horizon estimation, Nonlinear state estimation, Nonlinear systems, Robust stability
ASJC Scopus subject areas
- Engineering(all)
- Electrical and Electronic Engineering
- Engineering(all)
- Control and Systems Engineering
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: Automatica, Vol. 79, 01.05.2017, p. 306-314.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Nonlinear moving horizon estimation in the presence of bounded disturbances
AU - Müller, Matthias A.
N1 - Publisher Copyright: © 2017 Elsevier Ltd Copyright: Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/5/1
Y1 - 2017/5/1
N2 - In this paper, we propose a new moving horizon estimator for nonlinear detectable systems. Similar to a recently proposed full information estimator, the corresponding cost function contains an additional max-term compared to more standard least-squares type approaches. We show that robust global asymptotic stability in case of bounded disturbances and convergence of the estimation error in case of vanishing disturbances can be established. Second, we show that the same results hold for a standard least-squares type moving horizon estimator, which so far has not been proven even in the full information estimation case. An additional advantage of the proposed estimators is that a suitable prior weighting appearing in the cost function can explicitly be determined offline, which is not the case in various existing approaches.
AB - In this paper, we propose a new moving horizon estimator for nonlinear detectable systems. Similar to a recently proposed full information estimator, the corresponding cost function contains an additional max-term compared to more standard least-squares type approaches. We show that robust global asymptotic stability in case of bounded disturbances and convergence of the estimation error in case of vanishing disturbances can be established. Second, we show that the same results hold for a standard least-squares type moving horizon estimator, which so far has not been proven even in the full information estimation case. An additional advantage of the proposed estimators is that a suitable prior weighting appearing in the cost function can explicitly be determined offline, which is not the case in various existing approaches.
KW - Moving horizon estimation
KW - Nonlinear state estimation
KW - Nonlinear systems
KW - Robust stability
UR - http://www.scopus.com/inward/record.url?scp=85014160082&partnerID=8YFLogxK
U2 - 10.1016/j.automatica.2017.01.033
DO - 10.1016/j.automatica.2017.01.033
M3 - Article
VL - 79
SP - 306
EP - 314
JO - Automatica
JF - Automatica
SN - 0005-1098
ER -