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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 2962671, 7 pages
Research Article

Rigid Body Inertia Estimation Using Extended Kalman and Savitzky-Golay Filters

1LG Electronics, Seoul 08592, Republic of Korea
2Korea Aerospace University, Goyang 10540, Republic of Korea

Received 24 December 2015; Accepted 24 March 2016

Academic Editor: Anton V. Doroshin

Copyright © 2016 Donghoon Kim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Inertia properties of rigid body such as ground, aerial, and space vehicles may be changed by several occasions, and this variation of the properties influences the control accuracy of the rigid body. For this reason, accurate inertia properties need to be obtained for precise control. An estimation process is required for both noisy gyro measurements and the time derivative of the gyro measurements. In this paper, an estimation method is proposed for having reliable estimates of inertia properties. First, the Euler equations of motion are reformulated to obtain a regressor matrix. Next, the extended Kalman filter is adopted to reduce the noise effects in gyro angular velocity measurements. Last, the inertia properties are estimated using linear least squares. To achieve reliable and accurate angular accelerations, a Savitzky-Golay filter based on an even number sampled data is utilized. Numerical examples are presented to demonstrate the performance of the proposed algorithm for the case of a space vehicle. The numerical simulation results show that the proposed algorithm provides accurate inertia property estimates in the presence of noisy measurements.