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

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

*Corresponding author for this work

Research output: Contribution to journalConference articleScientificpeer-review

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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.

Original languageEnglish
Pages (from-to)10503-10508
Number of pages6
JournalIFAC-PapersOnLine
Volume56
Issue number2
DOIs
Publication statusPublished - 2023
Event22nd IFAC World Congress - Yokohama, Japan
Duration: 9 Jul 202314 Jul 2023

Keywords

  • Application of mechatronic principles
  • Motion control systems
  • Smart structures
  • Vibration Control

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