Fault estimation and accommodation for virtual sensor bias fault in image-based visual servoing using particle filter

Van, M. ORCID: 0000-0001-9616-6061, Ge, S.S. and Ceglarek, D., 2017. Fault estimation and accommodation for virtual sensor bias fault in image-based visual servoing using particle filter. IEEE Transactions on Industrial Informatics, PP (99). ISSN 1551-3203

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Abstract

This study develops a fault estimation and accommodation scheme for the image-based visual servoing (IBVS) system to eliminate the effects of the faults due to the image feature extraction task, which is named as bias virtual sensor fault. First, a bias virtual sensor fault in visual servoing is declared. Then, fault diagnosis (FD), which includes fault detection, isolation and estimation, is designed based on the means of particle filter (PF). Finally, a fault accommodation law is developed based on the information obtained from the fault estimation to compensate for the effects of the fault in the system. The proposed fault estimation and accommodation is verified through simulation and experimental studies, and the results show that the system can estimate and eliminate the unknown fault effects effectively.

Item Type:	Journal article
Publication Title:	IEEE Transactions on Industrial Informatics
Creators:	Van, M., Ge, S.S. and Ceglarek, D.
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Date:	6 July 2017
Volume:	PP
Number:	99
ISSN:	1551-3203
Identifiers:	Number Type 10.1109/TII.2017.2723930 DOI
Divisions:	Schools > School of Science and Technology
Record created by:	Linda Sullivan
Date Added:	12 Jul 2017 10:54
Last Modified:	12 Jul 2017 10:54
URI:	https://irep.ntu.ac.uk/id/eprint/31224

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