Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 244-250 |
| Seitenumfang | 7 |
| Fachzeitschrift | IFAC-PapersOnLine |
| Jahrgang | 54 |
| Ausgabenummer | 6 |
| Frühes Online-Datum | 9 Sept. 2021 |
| Publikationsstatus | Veröffentlicht - 2021 |
| Veranstaltung | 7th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2021) - Bratislava, Slowakei Dauer: 11 Juli 2021 → 14 Juli 2021 Konferenznummer: 7 |
Abstract
We present an approach for state and parameter estimation in retinal laser treatment by a novel setup where both measurement and heating is performed by a single laser. In this medical application, the temperature that is induced by the laser in the patient's eye is critical for a successful and safe treatment. To this end, we pursue a model-based approach using a model given by a heat diffusion equation on a cylindrical domain, where the source term is given by the absorbed laser power. The model is parametric in the sense that it involves an absorption coefficient, which depends on the treatment spot and plays a central role in the input-output behavior of the system. After discretization, we apply a particularly suited parametric model order reduction to ensure real-time tractability while retaining parameter dependence. We augment known state estimation techniques, i.e., extended Kalman filtering and moving horizon estimation, with parameter estimation to estimate the absorption coefficient and the current state of the system. Eventually, we show first results for simulated and experimental data from porcine eyes. We find that, regarding convergence speed, the moving horizon estimation slightly outperforms the extended Kalman filter on measurement data in terms of parameter and state estimation, however, on simulated data the results are very similar.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
Zitieren
- Standard
- Harvard
- Apa
- Vancouver
- BibTex
- RIS
in: IFAC-PapersOnLine, Jahrgang 54, Nr. 6, 2021, S. 244-250.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - State and parameter estimation for model-based retinal laser treatment
AU - Kleyman, Viktoria
AU - Schaller, Manuel
AU - Wilson, Mitsuru
AU - Mordmüller, Mario
AU - Brinkmann, Ralf
AU - Worthmann, Karl
AU - Müller, Matthias A.
N1 - Conference code: 7
PY - 2021
Y1 - 2021
N2 - We present an approach for state and parameter estimation in retinal laser treatment by a novel setup where both measurement and heating is performed by a single laser. In this medical application, the temperature that is induced by the laser in the patient's eye is critical for a successful and safe treatment. To this end, we pursue a model-based approach using a model given by a heat diffusion equation on a cylindrical domain, where the source term is given by the absorbed laser power. The model is parametric in the sense that it involves an absorption coefficient, which depends on the treatment spot and plays a central role in the input-output behavior of the system. After discretization, we apply a particularly suited parametric model order reduction to ensure real-time tractability while retaining parameter dependence. We augment known state estimation techniques, i.e., extended Kalman filtering and moving horizon estimation, with parameter estimation to estimate the absorption coefficient and the current state of the system. Eventually, we show first results for simulated and experimental data from porcine eyes. We find that, regarding convergence speed, the moving horizon estimation slightly outperforms the extended Kalman filter on measurement data in terms of parameter and state estimation, however, on simulated data the results are very similar.
AB - We present an approach for state and parameter estimation in retinal laser treatment by a novel setup where both measurement and heating is performed by a single laser. In this medical application, the temperature that is induced by the laser in the patient's eye is critical for a successful and safe treatment. To this end, we pursue a model-based approach using a model given by a heat diffusion equation on a cylindrical domain, where the source term is given by the absorbed laser power. The model is parametric in the sense that it involves an absorption coefficient, which depends on the treatment spot and plays a central role in the input-output behavior of the system. After discretization, we apply a particularly suited parametric model order reduction to ensure real-time tractability while retaining parameter dependence. We augment known state estimation techniques, i.e., extended Kalman filtering and moving horizon estimation, with parameter estimation to estimate the absorption coefficient and the current state of the system. Eventually, we show first results for simulated and experimental data from porcine eyes. We find that, regarding convergence speed, the moving horizon estimation slightly outperforms the extended Kalman filter on measurement data in terms of parameter and state estimation, however, on simulated data the results are very similar.
KW - Model predictive control in medicine applications
KW - Model reduction
KW - Modeling
KW - Moving horizon estimation
KW - Nonlinear observers and filter design
KW - Parameter-varying systems
UR - http://www.scopus.com/inward/record.url?scp=85117932920&partnerID=8YFLogxK
U2 - 10.1016/j.ifacol.2021.08.552
DO - 10.1016/j.ifacol.2021.08.552
M3 - Conference article
AN - SCOPUS:85117932920
VL - 54
SP - 244
EP - 250
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
SN - 2405-8963
IS - 6
T2 - 7th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2021)
Y2 - 11 July 2021 through 14 July 2021
ER -