@inproceedings{5d0c90e484af430ab53270bf9ee06dce,
title = "Recursive Least Squares Parameter Estimation for DC Fault Detection and Localization",
abstract = "The advancement of modern aircraft seeks to place a higher priority on the electrical power systems to execute flight operations. Transitioning to aircraft with a larger dependence on these systems is advantageous because they increase reliability, maintainability, and cost efficiency. This requires an intelligent power system that is capable of not only powering the aircraft at ideal conditions, but also detecting faults and autonomously redistributing power to flight-critical electrical loads. This paper investigates how to detect parallel faults using recursive least squares estimation. Results indicate how estimation is affected by system variables.",
keywords = "DC Fault Detection, Intelligent Power System, Recursive Least Squares, RLS",
author = "Kellen O'Shea and Tsao, \{Bang Hung\} and Luis Herrera and Chad Miller",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE National Aerospace and Electronics Conference, NAECON 2019 ; Conference date: 15-07-2019 Through 19-07-2019",
year = "2019",
month = jul,
doi = "10.1109/NAECON46414.2019.9057890",
language = "English",
series = "Proceedings of the IEEE National Aerospace Electronics Conference, NAECON",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "7--10",
booktitle = "2019 IEEE National Aerospace and Electronics Conference, NAECON 2019",
address = "United States",
}