A SUB-OPTIMAL KALMAN FILTERING FOR DISCRETE-TIME LTI SYSTEMS WITH LOSS OF DATA

Naeem Khan, Sajjad Fekri, Dawei Gu

Abstract

In this paper a sub-optimal Kalman filter estimator is designed for the plants subject to loss of data or insufficient observation. The methodology utilized is based on the closed-loop compensation algorithm which is computed through the so-called Modified Linear Prediction Coefficient (MLPC) observation scheme. The proposed approach is aimed at the artificial observation vector which in fact corrects the prediction cycle when loss of data occurs. A non-trivial mass-spring-dashpot case study is also selected to demonstrate some of the key issues that arise when using the proposed sub-optimal filtering algorithm under missing data.

References

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Paper Citation


in Harvard Style

Khan N., Fekri S. and Gu D. (2010). A SUB-OPTIMAL KALMAN FILTERING FOR DISCRETE-TIME LTI SYSTEMS WITH LOSS OF DATA . In Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 978-989-8425-02-7, pages 201-207. DOI: 10.5220/0002953402010207


in Bibtex Style

@conference{icinco10,
author={Naeem Khan and Sajjad Fekri and Dawei Gu},
title={A SUB-OPTIMAL KALMAN FILTERING FOR DISCRETE-TIME LTI SYSTEMS WITH LOSS OF DATA},
booktitle={Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2010},
pages={201-207},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002953402010207},
isbn={978-989-8425-02-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - A SUB-OPTIMAL KALMAN FILTERING FOR DISCRETE-TIME LTI SYSTEMS WITH LOSS OF DATA
SN - 978-989-8425-02-7
AU - Khan N.
AU - Fekri S.
AU - Gu D.
PY - 2010
SP - 201
EP - 207
DO - 10.5220/0002953402010207