Esin BABACAN KOKSAL, İ. DOROSLOVACKI MİLOS, Levent ÖZBEK

MODIFIED UNSCENTED KALMAN FILTER FOR NONLINEAR SYSTEMS

The Extended Kalman Filter (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 (UKF) is introduced. In this paper, we propose a new modified Unscented Kalman Filter (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 (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 problem

Keywords:

Nonlinear Dynamic System System idendification, Extended Kalman Filter, Unscented Kalman Filter.,

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Current Address: Esin Köksal Babacan, Ankara University, Department of Statistics, Faculty of Science, 06100 Tandoğan, Ankara-TURKEY

Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics-Cover

ISSN: 1303-5991
Yayın Aralığı: Yılda 4 Sayı
Başlangıç: 1948
Yayıncı: Ankara Üniversitesi

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