DocumentCode
189035
Title
A robust unscented fusion filter using fuzzy adaptation rule
Author
Chul Woo Kang ; Chan Park
Author_Institution
Autom. & Syst. Res. Inst., Seoul Nat. Univ., Seoul, South Korea
fYear
2014
fDate
24-27 June 2014
Firstpage
1373
Lastpage
1378
Abstract
This paper presents a new robust estimation approach for nonlinear systems. Former approaches to robust nonlinear estimation such as the unscented H ∞ filter(UHF) [1] perform well on in disturbed nonlinear systems. However, with regard to undisturbed systems, the performance of robust nonlinear filters has proven inferior to that of conventional nonlinear filters. In this paper, a new filter is proposed which performs well on both disturbed and undisturbed systems by integrating a UHF and an unscented Kalman filter (UKF). The proposed filter uses a hybrid filter structure for the proper integration of the two local filters; a fuzzy-based mode adaptation rule is also implemented to improve performance.
Keywords
Kalman filters; fuzzy set theory; nonlinear control systems; nonlinear estimation; nonlinear filters; robust control; UHF; disturbed nonlinear systems; fuzzy adaptation rule; fuzzy-based mode adaptation rule; nonlinear systems; robust estimation approach; robust nonlinear estimation; robust unscented fusion filter; unscented Kalman filter; Estimation; Filtering algorithms; Filtering theory; Finite impulse response filters; Kalman filters; Nonlinear filters; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (ECC), 2014 European
Conference_Location
Strasbourg
Print_ISBN
978-3-9524269-1-3
Type
conf
DOI
10.1109/ECC.2014.6862320
Filename
6862320
Link To Document