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 :
بازگشت