Robust Fault Estimation on a real quadrotor UAV using optimized Adaptive Thau Observer

Zhaohui Cen, Hassan Noura, Younes Al Younes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

As a result of modeling uncertainties, data decade unbalanceand noise, Fault Estimation (FE) for real quadrotor is rough with low accuracy when model observer based FE scheme - Adaptive Thau Observer(ATO) is applied. Based on these issues, this paper proposes a comprehensive optimization approach on FE accuracy for quadrotor using ATO. First, the ATO observer is improved by adding unmolded terms with parameters derived from identification. Secondly, a data adjustment based on amplifying and reducing is introduced to overcome the data decade unbalance. Thirdly, the Infinite Impulse Response (IIR) filter is utilized to decrease the noise in measurement signals. Finally, experiments for injecting the rotor fault have been carried out to show the effectiveness of the proposed optimization method and the results are discussed.

Original languageEnglish
Title of host publication2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Conference Proceedings
Pages550-556
Number of pages7
DOIs
Publication statusPublished - 2 Sep 2013
Event2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Atlanta, GA, United States
Duration: 28 May 201328 May 2013

Publication series

Name2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Conference Proceedings

Other

Other2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013
CountryUnited States
CityAtlanta, GA
Period28/5/1328/5/13

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ASJC Scopus subject areas

  • Aerospace Engineering

Cite this

Cen, Z., Noura, H., & Younes, Y. A. (2013). Robust Fault Estimation on a real quadrotor UAV using optimized Adaptive Thau Observer. In 2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Conference Proceedings (pp. 550-556). [6564732] (2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Conference Proceedings). https://doi.org/10.1109/ICUAS.2013.6564732