Fault tolerant attitude estimation for pico satellites using robust adaptive UKF

Date

2012-10-09

Author

Söken, Halil Ersin

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

142
views

0
downloads

Unscented Kalman Filter (UKF) is a filtering algorithm which gives sufficiently good estimation results for estimation problems of nonlinear systems even when high nonlinearity is in question. However, in case of system uncertainty or measurements malfunctions the UKF becomes to be inaccurate and diverges by time. This study, introduces a fault tolerant attitude estimation algorithm for pico satellites. The algorithm uses a Robust Adaptive Unscented Kalman Filter (RAUKF) which performs correction for process noise covariance (Q-adaptation) or measurement noise covariance (R-adaptation) depending on the type of the fault. By the use of a newly proposed adaptation scheme for the conventional UKF algorithm, the fault is detected; isolated and the essential adaptation procedure is followed in accordance with the fault type. The proposed algorithm is tested as a part of the attitude estimation algorithm of a pico satellite, a satellite type for which computational convenience is necessary because of the design limitations. © 2012 IFAC.

URI

https://hdl.handle.net/11511/69788

DOI

https://doi.org/10.3182/20120829-3-mx-2028.00064

Collections

Department of Aerospace Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Adaptive Fading UKF with Q-Adaptation: Application to Picosatellite Attitude Estimation Söken, Halil Ersin (American Society of Civil Engineers (ASCE), 2013-07-01) The unscented Kalman filter (UKF) is a filtering algorithm that gives sufficiently good estimation results for estimation problems of nonlinear systems even when high nonlinearity is in question. However, in the case of system uncertainty the UKF becomes inaccurate and diverges in time. In other words, if any change occurs in the process noise covariance, which is known a priori, the filter fails. This study introduces a novel adaptive fading UKF algorithm based on the correction of process noise covariance...
Robust adaptive unscented Kalman filter for attitude estimation of pico satellites Hacızade, Cengiz; Söken, Halil Ersin (Wiley, 2014-02-01) Unscented Kalman filter (UKF) is a filtering algorithm that gives sufficiently good estimation results for the estimation problems of nonlinear systems even when high nonlinearity is in question. However, in case of system uncertainty or measurement malfunctions, the UKF becomes inaccurate and diverges by time. This study introduces a fault-tolerant attitude estimation algorithm for pico satellites. The algorithm uses a robust adaptive UKF, which performs correction for the process noise covariance (Q-adapt...
Reconfigurable UKF for in-flight magnetometer calibration and attitude parameter estimation Söken, Halil Ersin (2011-01-01) In this study a reconfigurable unscented Kalman filter (UKF) based algorithm for the estimation of magnetometer biases and scale factors is proposed as a part of the attitude estimation scheme of a pico satellite. Algorithm is composed of two stages; in first stage UKF estimates magnetometer biases and scale factors as well as six attitude parameters of the satellite. Differently from the existing algorithms, scale factors are not treated together with the other parameters as a part of the state vector; thr...
Estimation of pico-satellite attitude dynamics and external torques via Unscented Kalman Filter Söken, Halil Ersin (FapUNIFESP (SciELO), 2014-01-01) In this study, an Unscented Kalman Filter (UKF) algorithm is designed for estimating the attitude of a picosatellite and the in-orbit external disturbance torques. The estimation vector is formed by the satellite's attitude, angular rates, and the unknown constant components of the external disturbance torques acting on the satellite. The gravity gradient torque, residual magnetic moment, sun radiation pressure and aerodynamic drag are all included in the estimated external disturbance torque vector. The sa...
Fault tolerant estimation of autonomous underwater vehicle dynamics via robust UKF Hajiyev, Chingiz; Ata, Melih; Dinc, Mustafa; Söken, Halil Ersin (2012-07-30) This article is basically focused on application of the Unscented Kalman Filter (UKF) algorithm to the estimation of high speed an autonomous underwater vehicle (AUV) dynamics. In the normal operation conditions of AUV, conventional UKF gives sufficiently good estimation results. However, if the measurements are not reliable because of any kind of malfunction in the estimation system, UKF gives inaccurate results and diverges by time. This study, introduces Robust Unscented Kalman Filter (RUKF) algorithms w...

Citation Formats

H. E. Söken, “Fault tolerant attitude estimation for pico satellites using robust adaptive UKF,” 2012, vol. 8, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69788.