Evaluation of recursive Bayesian filters for modal contribution estimation in high-tech compliant mechanisms

de Bruin, P. E.; Kaczmarek, M.B.; Kok, M.; Hassan HosseinNia, S.

doi:10.1016/j.ifacol.2023.10.1070

Evaluation of recursive Bayesian filters for modal contribution estimation in high-tech compliant mechanisms

Title

Evaluation of recursive Bayesian filters for modal contribution estimation in high-tech compliant mechanisms

Author

de Bruin, P. E. (Student TU Delft)
Kaczmarek, M.B. (TU Delft Mechatronic Systems Design)
Kok, M. (TU Delft Team Manon Kok)
Hassan HosseinNia, S. (TU Delft Mechatronic Systems Design)

Date

2023

Abstract

This study evaluates three recursive Bayesian input and state estimation algorithms, as introduced in the field of Structural Health Monitoring, for estimating modal contributions for high-tech compliant mechanisms. The aim of estimating modal contributions is the use for active vibration control. High-tech compliant motion stages allow for different sensor configurations, making new and interesting performance evaluations of these filters possible. The algorithms used, namely, the Augmented Kalman Filter (AKF), Dual Kalman Filter (DKF) and Gilijns de Moor Filter (GDF) are implemented on a compliant motion stage for guidance flexure deformation estimation. Our results show the GDF performs overall best, with good estimation performance and real-world tuning capability.

Subject

Application of mechatronic principles
Motion control systems
Smart structures
Vibration Control

To reference this document use:

http://resolver.tudelft.nl/uuid:8cafb055-968e-4ea6-9e84-ed8bf928d84b

DOI

https://doi.org/10.1016/j.ifacol.2023.10.1070

Source

IFAC-PapersOnLine, 56 (2), 10503-10508

Event

22nd IFAC World Congress, 2023-07-09 → 2023-07-14, Yokohama, Japan

Part of collection

Institutional Repository