A proposal for a nonlinear Kalman filter using state dependent linear representation system and its performance analysis by numerical simulations

Author:

ARAKI Nozomu1,KAWAGUCHI Natsuki1,SATO Takao1,KONISHI Yasuo1

Affiliation:

1. Graduate School of Engineering, University of Hyogo

Publisher

Japan Society of Mechanical Engineers

Reference10 articles.

1. Adachi, S. and Maruta, I., Fundamentals of Kalman Filter (2012), Tokyo Denki University Press (in Japanese).

2. Athans, M., Wishner, R. P. and Bertolini, A., Suboptimal state estimation for continuous-time nonlinear systems from discrete noisy measurements, IEEE Transactions on Automatic Control, Vol.AC-13, No.5 (1968), pp.504–514.

3. Grewal, M. S. and Andrews, A. P., Kalman Filtering: Theory and Practice Using MATLAB, Second Edition (2001), Wiley-Interscience.

4. Haessig, D. A. and Friedland, B., State dependent differential Riccati equation for nonlinear estimation and control, Proc. of 15th IFAC World Congress, Vol.35, Issue 1 (2002), pp.405–410.

5. Jaganath, C., Ridley, A. and Bernstein, D. S., A SDRE-based asymptotic observer for nonlinear discrete-time systems, Proc. of 2005 American Control Conference (2005), pp.3630–3635.

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