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https://hdl.handle.net/11499/36972
Title: | Active fault tolerant control for high-precision positioning of a non-contact mode uncertain atomic force microscopy | Authors: | Çetin, Meriç Beyhan, Selami |
Keywords: | Atomic force microscopy EKF fault tolerant control joint state and parameter estimation NMPC noise disturbance UKF End effectors Fault tolerance Kalman filters Parameter estimation Uncertainty analysis Active fault tolerant control Extended Kalman filtering Fault tolerant controllers High precision positioning Model based controller design Model predictive controllers Unscented Kalman Filter Unscented Kalman filtering Controllers |
Publisher: | SAGE Publications Ltd | Abstract: | A non-contact mode atomic force microscope with chaotic dynamics may exposed to unknown faults, disturbances or uncertain parameters that are not always be compensated using classical control methods. Therefore, a fault tolerant controller must be designed for accurate tracking of the tip-position of the end-effector. In this paper, first, an unscented Kalman filter is designed for joint estimation of the states and parameters for an atomic force microscopy under process noise. The velocity of the end-effector, sample height and unknown fault are simultaneously estimated by measuring the tip position of randomly excited microscopy. Second, unscented Kalman filtering based model predictive controller is proposed for the accurate tracking of the tip-position. To prevent the disadvantage of the model-based controller design, an uncertainty or unknown fault function of the system is estimated by unscented Kalman filter such that the unmodeled dynamics of the system are compensated while the control signal is produced. Note that the controller voltage being applied to the microscopy is produced based on the estimated states and parameters of the atomic force microscopy. The numerical applications present that satisfactory tracking performance for tip position is obtained by the proposed fault tolerant controller such that extended Kalman filtering-based tracking results are also compared and discussed. © The Author(s) 2020. | URI: | https://hdl.handle.net/11499/36972 https://doi.org/10.1177/0142331220923771 |
ISSN: | 0142-3312 |
Appears in Collections: | Mühendislik Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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