Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering

Research and Application of Moving Tracking of Stewart Based on Multi-innovation EKF Algorithm

Authors
Sujian Sheng, Bo Yang, Pinle Qin, Xiaoqing Chen
Corresponding Author
Sujian Sheng
Available Online February 2016.
DOI
10.2991/iccsae-15.2016.90How to use a DOI?
Keywords
Extend Kalman Filter; Multi-innovation; Multi-innovation Extend Kalman Filter;Simulation analyses
Abstract

Because of the low estimation accuracy of normal extended Kalman Filter in strong nonlinear system, an improved extended Kalman Filter (MI-EKF) is presented to solve the problem, and the filtering accuracy is greatly improved. In this paper, multi-innovation theory is applied to EKF, and the multi-innovation EKF (MI-EKF) is proposed. MI-EKF has better precision and stability, because MI-EKF considers not only the current measured value, but also give full consideration to the time before state of motion. Finally, the improvement algorithm is used the moving tracking of six degree freedom stewart motion platform, the simulation results show that the improved MI-EKF algorithm is superior to the standard EKFalgorithm.

Copyright
© 2016, 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/).

Download article (PDF)

Volume Title
Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
Series
Advances in Computer Science Research
Publication Date
February 2016
ISBN
978-94-6252-156-8
ISSN
2352-538X
DOI
10.2991/iccsae-15.2016.90How to use a DOI?
Copyright
© 2016, 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/).

Cite this article

TY  - CONF
AU  - Sujian Sheng
AU  - Bo Yang
AU  - Pinle Qin
AU  - Xiaoqing Chen
PY  - 2016/02
DA  - 2016/02
TI  - Research and Application of Moving Tracking of Stewart Based on Multi-innovation EKF Algorithm
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 478
EP  - 485
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.90
DO  - 10.2991/iccsae-15.2016.90
ID  - Sheng2016/02
ER  -