@inproceedings{0250f883e409403c82cd3a9d07dfa1c1,
title = "A measurement-based fault detection approach applied to monitor robots swarm",
abstract = "Swarm robotics requires continuous monitoring to detect abnormal events and to sustain normal operations. Indeed, swarm robotics with one or more faulty robots leads to degradation of performances complying with the target requirements. This paper present an innovative data-driven fault detection method for monitoring robots swarm. The method combines the flexibility of principal component analysis (PCA) models and the greater sensitivity of the exponentially-weighted moving average control chart to incipient changes. We illustrate through simulated data collected from the ARGoS simulator that a significant improvement in fault detection can be obtained by using the proposed methods as compared to the use of the conventional PCA-based methods.",
author = "Belkacem Khaldi and Fouzi Harrou and Ying Sun and Foudil Cherif",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 6th International Conference on Systems and Control, ICSC 2017 ; Conference date: 07-05-2017 Through 09-05-2017",
year = "2017",
month = jun,
day = "23",
doi = "10.1109/ICoSC.2017.7958703",
language = "English (US)",
series = "2017 6th International Conference on Systems and Control, ICSC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "21--26",
editor = "Driss Mehdi and Said Drid and Abdelouahab Aitouche",
booktitle = "2017 6th International Conference on Systems and Control, ICSC 2017",
address = "United States",
}