Robust Estimation of UAV Dynamics in the Presence of Measurement Faults

Date

2012-01-01

Author

Hacızade, Cengiz
Söken, Halil Ersin

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This study introduces a robust Kalman filter (RKF) with a filter-gain correction for cases of measurement malfunctions. Using defined variables called measurement-noise scale factors, the faulty measurements are taken into consideration with a small weight and the estimations are corrected without affecting the characteristics of the accurate ones. In this study, RKF algorithms with single and multiple scale factors are proposed and applied for the state estimation process of an unmanned aerial vehicle (UAV) platform. The results of these algorithms are compared for different types of measurement faults, and recommendations for their utilization are given. DOI: 10.1061/(ASCE)AS.1943-5525.0000095. (C) 2012 American Society of Civil Engineers.

Subject Keywords

Mechanical Engineering, General Materials Science, Civil and Structural Engineering, Aerospace Engineering

URI

https://hdl.handle.net/11511/69769

Journal

JOURNAL OF AEROSPACE ENGINEERING

DOI

https://doi.org/10.1061/(asce)as.1943-5525.0000095

Collections

Department of Aerospace Engineering, Article

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Citation Formats

C. Hacızade and H. E. Söken, “Robust Estimation of UAV Dynamics in the Presence of Measurement Faults,” JOURNAL OF AEROSPACE ENGINEERING, pp. 80–89, 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69769.