Multi-innovation Self-tuning Kalman Filter with Unknown Parameters Systems

DOI

10.2991/ipemec-15.2015.146How to use a DOI?

Keywords

multi-innovation; Kalman filter; self-tuning filter; least squares

Abstract

Based on the multi-innovation least squares algorithm and the optimal Kalman filtering method, a new multi-innovation self-tuning Kalman filtering algorithm is presented for systems with unknown model parameters. It avoids the flaw of classical Kalman filter which needs to accurately know the model parameter in system. A simulation example shows its effectiveness.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jun Yue
AU  - Ying Shi
PY  - 2015/05
DA  - 2015/05
TI  - Multi-innovation Self-tuning Kalman Filter with Unknown Parameters Systems
BT  - Proceedings of the 2015 International Power, Electronics and Materials Engineering Conference
PB  - Atlantis Press
SP  - 788
EP  - 792
SN  - 2352-5401
UR  - https://doi.org/10.2991/ipemec-15.2015.146
DO  - 10.2991/ipemec-15.2015.146
ID  - Yue2015/05
ER  -