Details
| Original language | English |
|---|---|
| Pages (from-to) | 341-348 |
| Number of pages | 8 |
| Journal | IFAC-PapersOnLine |
| Volume | 58 |
| Issue number | 18 |
| Early online date | 25 Sept 2024 |
| Publication status | Published - 2024 |
| Event | 8th IFAC Conference on Nonlinear Model Predictive Control, NMPC 2024 - Kyoto, Japan Duration: 21 Aug 2024 → 24 Aug 2024 |
Abstract
We propose a moving horizon estimation scheme for estimating the states and time-varying parameters of nonlinear systems. We consider the case where observability of the parameters depends on the excitation of the system and may be absent during operation, with the parameter dynamics fulfilling a weak incremental bounded-energy bounded-state property to ensure boundedness of the estimation error (with respect to the disturbance energy). The proposed estimation scheme involves a standard quadratic cost function with an adaptive regularization term depending on the current parameter observability. We develop robustness guarantees for the overall estimation error that are valid for all times, and that improve the more often the parameters are detected to be observable during operation. The theoretical results are illustrated by a simulation example.
Keywords
- Moving horizon estimation, parameter estimation, state estimation
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
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In: IFAC-PapersOnLine, Vol. 58, No. 18, 2024, p. 341-348.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Moving horizon estimation for nonlinear systems with time-varying parameters
AU - Schiller, Julian D.
AU - Müller, Matthias A.
N1 - Publisher Copyright: Copyright © 2024 The Authors.
PY - 2024
Y1 - 2024
N2 - We propose a moving horizon estimation scheme for estimating the states and time-varying parameters of nonlinear systems. We consider the case where observability of the parameters depends on the excitation of the system and may be absent during operation, with the parameter dynamics fulfilling a weak incremental bounded-energy bounded-state property to ensure boundedness of the estimation error (with respect to the disturbance energy). The proposed estimation scheme involves a standard quadratic cost function with an adaptive regularization term depending on the current parameter observability. We develop robustness guarantees for the overall estimation error that are valid for all times, and that improve the more often the parameters are detected to be observable during operation. The theoretical results are illustrated by a simulation example.
AB - We propose a moving horizon estimation scheme for estimating the states and time-varying parameters of nonlinear systems. We consider the case where observability of the parameters depends on the excitation of the system and may be absent during operation, with the parameter dynamics fulfilling a weak incremental bounded-energy bounded-state property to ensure boundedness of the estimation error (with respect to the disturbance energy). The proposed estimation scheme involves a standard quadratic cost function with an adaptive regularization term depending on the current parameter observability. We develop robustness guarantees for the overall estimation error that are valid for all times, and that improve the more often the parameters are detected to be observable during operation. The theoretical results are illustrated by a simulation example.
KW - Moving horizon estimation
KW - parameter estimation
KW - state estimation
UR - http://www.scopus.com/inward/record.url?scp=85206101151&partnerID=8YFLogxK
U2 - 10.1016/j.ifacol.2024.09.053
DO - 10.1016/j.ifacol.2024.09.053
M3 - Conference article
AN - SCOPUS:85206101151
VL - 58
SP - 341
EP - 348
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
SN - 2405-8971
IS - 18
T2 - 8th IFAC Conference on Nonlinear Model Predictive Control, NMPC 2024
Y2 - 21 August 2024 through 24 August 2024
ER -