Details
| Original language | English |
|---|---|
| Pages (from-to) | 6759-6764 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| Volume | 56 |
| Issue number | 2 |
| Early online date | 22 Nov 2022 |
| Publication status | Published - 2023 |
Abstract
Keywords
- eess.SY, cs.SY, incremental system properties, nonlinear systems, Moving horizon estimation, parametric uncertainties, parameter estimation, state estimation
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
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In: IFAC-PapersOnLine, Vol. 56, No. 2, 2023, p. 6759-6764.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - A moving horizon state and parameter estimation scheme with guaranteed robust convergence
AU - Schiller, Julian D.
AU - Müller, Matthias A.
N1 - Publisher Copyright: Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
PY - 2023
Y1 - 2023
N2 - We propose a moving horizon estimation scheme for joint state and parameter estimation for nonlinear uncertain discrete-time systems. We establish robust exponential convergence of the combined estimation error subject to process disturbances and measurement noise. We employ a joint incremental input/output-to-state stability (δ-IOSS) Lyapunov function to characterize nonlinear detectability for the states and (constant) parameters of the system. Sufficient conditions for the construction of a joint δ-IOSS Lyapunov function are provided for a special class of nonlinear systems using a persistence of excitation condition. The theoretical results are illustrated by a numerical example.
AB - We propose a moving horizon estimation scheme for joint state and parameter estimation for nonlinear uncertain discrete-time systems. We establish robust exponential convergence of the combined estimation error subject to process disturbances and measurement noise. We employ a joint incremental input/output-to-state stability (δ-IOSS) Lyapunov function to characterize nonlinear detectability for the states and (constant) parameters of the system. Sufficient conditions for the construction of a joint δ-IOSS Lyapunov function are provided for a special class of nonlinear systems using a persistence of excitation condition. The theoretical results are illustrated by a numerical example.
KW - eess.SY
KW - cs.SY
KW - incremental system properties
KW - nonlinear systems
KW - Moving horizon estimation
KW - parametric uncertainties
KW - parameter estimation
KW - state estimation
UR - http://www.scopus.com/inward/record.url?scp=85180623064&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2211.09053
DO - 10.48550/arXiv.2211.09053
M3 - Article
VL - 56
SP - 6759
EP - 6764
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
SN - 2405-8963
IS - 2
ER -