Stability of the adaptive fading extended Kalman filter with the matrix forgetting factor

Cenker BİÇER; Esin KÖKSAL BABACAN; Levent ÖZBEK

Makale detayları

Stability of the adaptive fading extended Kalman filter with the matrix forgetting factor

Yazarlar:

Cenker BİÇER | Esin KÖKSAL BABACAN | Levent ÖZBEK

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2012 Vol.20 Issue 5, pp.819-833

Belge Tipi:

Makale

Yayın Tarihi:

4/2012

Belge Dili:

Türkçe

Document ID (Org No.):

2000743548

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

The extended Kalman filter is extensively used in nonlinear  state estimation problems.  As long as the system characteristics are  correctly known, the extended Kalman filter gives the best  performance.  However, when the system information is partially known  or incorrect, the extended Kalman filter may diverge or give biased  estimates.  An extensive number of works has been published to improve the performance of the extended Kalman filter.  Many researchers have proposed the introduction of a forgetting factor, both into the Kalman filter and the extended Kalman filter, to improve the performance. However, there are 2 fundamental problems with this approach: the incorporation of the optimal forgetting factor into the (extended) Kalman filter and the selection of the optimal forgetting factor. These problems have not yet been fully resolved and are still open problems in the field.  In this study, we propose a new adaptive fading extended Kalman filter with a matrix forgetting factor, and 2 methods are analyzed for the selection of the optimal forgetting factor.  The stability properties of the proposed filter are also investigated.  Results of the stability analysis show that the proposed filter is an exponential observer for nonlinear deterministic systems.  Additionally, the convergence speed of the filter is  simulated.

 

The extended Kalman filter is extensively used in nonlinear  state estimation problems.  As long as the system characteristics are  correctly known, the extended Kalman filter gives the best  performance.  However, when the system information is partially known  or incorrect, the extended Kalman filter may diverge or give biased  estimates.  An extensive number of works has been published to improve the performance of the extended Kalman filter.  Many researchers have proposed the introduction of a forgetting factor, both into the Kalman filter and the extended Kalman filter, to improve the performance. However, there are 2 fundamental problems with this approach: the incorporation of the optimal forgetting factor into the (extended) Kalman filter and the selection of the optimal forgetting factor. These problems have not yet been fully resolved and are still open problems in the field.  In this study, we propose a new adaptive fading extended Kalman filter with a matrix forgetting factor, and 2 methods are analyzed for the selection of the optimal forgetting factor.  The stability properties of the proposed filter are also investigated.  Results of the stability analysis show that the proposed filter is an exponential observer for nonlinear deterministic systems.  Additionally, the convergence speed of the filter is  simulated.

Makale detayları

Stability of the adaptive fading extended Kalman filter with the matrix forgetting factor

Yazarlar: Cenker BİÇER | Esin KÖKSAL BABACAN | Levent ÖZBEK

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2012 Vol.20 Issue 5, pp.819-833

Belge Tipi: Makale

Yayın Tarihi: 4/2012

Belge Dili: Türkçe

Document ID (Org No.): 2000743548

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Cenker BİÇER | Esin KÖKSAL BABACAN | Levent ÖZBEK

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2012 Vol.20 Issue 5, pp.819-833

Belge Tipi:

Makale

Yayın Tarihi:

4/2012

Belge Dili:

Türkçe

Document ID (Org No.):

2000743548

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632