Lateral imbalance detection on a UAV based on multiple models

Sajjad Fekri, Da-Wei Gu, Ian Postlethwaite

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    3 Citations (Scopus)


    This paper addresses a multiple-model based lateral imbalance detection methodology for an uninhabited air vehicle (UAV). Two critical imbalance failures are considered that are the failure-induced left aileron stuck and the centre-of-gravity shift along the y-axis. A bank of LTI Kalman filters are designed to detect the above lateral failures and a flight control law based on the model predictive control (MPC) theory is designed for the aircraft lateral directional dynamics. It is shown that the proposed multiple-model detection scheme is able to achieve an effective reconfiguration capability to provide the efficient handling qualities at the failure-free flight operating conditions whilst it maintains desirable performance at post-failure conditions. The results of the proposed multiple-model based fault reconfigurable scheme for the UAV flight dynamics are illustrated and validated through simulations
    Original languageEnglish
    Title of host publicationProceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference
    Place of PublicationPiscataway, NJ
    ISBN (Print)978-1424438716
    Publication statusPublished - 2009
    Event48th IEEE Conference on Decision and Control - Shanghai, China
    Duration: 29 Jan 2009 → …


    Conference48th IEEE Conference on Decision and Control
    Period29/01/09 → …


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