By Topic

A new data fusion method and its application to state estimation of nonlinear dynamic systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jae-Won Lee ; Syst. & Control Sector, Samsung Adv. Inst. of Technol., Suwon, South Korea ; Sukhan Lee

We propose a geometric data fusion (GDF) method using a perception-net which can provide error reducing, uncertainty management, and maintaining consistency. We propose a perception-net to design a state estimator for dynamic systems and apply the proposed geometric data fusion method to obtain the optimal estimate, propagate uncertainties and utilize the system knowledge. We present comparisons between the proposed estimator and the conventional estimators. It is also shown that the additional priori information on the system can be easily utilized in the proposed estimator to improve the performance. Through illustrative examples, it is verified that the proposed estimator presents better performances than existing filters and improves performances via utilizing system knowledge

Published in:

Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on  (Volume:4 )

Date of Conference: