- Communications Faculty of Sciences University Ankara Series A1 Mathematics and Statistics
- Volume:64 Issue:2
- MODIFIED UNSCENTED KALMAN FILTER FOR NONLINEAR SYSTEMS
MODIFIED UNSCENTED KALMAN FILTER FOR NONLINEAR SYSTEMS
Authors : Esin BABACAN KOKSAL, İ DOROSLOVACKI MİLOS, Levent ÖZBEK
Pages : 89-98
Doi:10.1501/Commua1_0000000736
View : 46 | Download : 6
Publication Date : 2015-08-01
Article Type : Research Paper
Abstract :The Extended Kalman Filter insert ignore into journalissuearticles values(EKF); is the often used filtering algorithm for nonlinear systems. But it does not usually produce desirable results. Recently a new nonlinear filtering algorithm named as Unscented Kalman Filter insert ignore into journalissuearticles values(UKF); is introduced. In this paper, we propose a new modified Unscented Kalman Filter insert ignore into journalissuearticles values(MUKF); algorithm for nonlinear stochastic systems that are linear in some components. These nonlinear systems can be considered as having linear subsystems with parameters and aim is to estimate the system parameters. In simulation study, performance of the EKF, its known variant Modified Extended Kalman Filter insert ignore into journalissuearticles values(MEKF);, UKF and the proposed MUKF is demonstrated for a nonlinear system that is linear in some components. The results show that MUKF gives the best solution for parameter identification problemKeywords : Nonlinear Dynamic System, System idendification, Extended Kalman Filter, Unscented Kalman Filter
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