![](/images/graphics-bg.png)
On-line parameters estimation of low scale SPSG using discrete Kalman Filters
المؤلفون المشاركون
Bin Tunisi, A.
Larakeb, M.
Djeghloud, H.
المصدر
العدد
المجلد 12، العدد 4 (31 ديسمبر/كانون الأول 2016)، ص ص. 770-785، 16ص.
الناشر
تاريخ النشر
2016-12-31
دولة النشر
الجزائر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
Parametric identification techniques are applied in year’s space from electrical machines.
Many of these techniques are verging on each other in this field.
In fact, certain techniques are more adapted to a recorded time parametric identification and which are called ‘off-line methods’.
The off-line me other techniques are more suitable for a real time estimation of the parameters and are known as ‘on-line methods’.
The on-line methods concern mainly the case where the machine is functioning under load conditions, but both methods (off optimization algorithm to minimize the error between the real an this article, the study was carried out on a salient KW.
At first, the performance of experimental parametric identification using off presented; subsequently, different estimators were applied to on The discrete Kalman filter (DKF) is the estimator applied in this its traditional form (DTKF) for linear systems or in its extended form (DEKF) when the system is nonlinear.
Another attractive application of the DKF is when it is biased (DBEKF).
The consideration of the bias makes it possible between measured and estimated values of the system state variable; accordingly, the normalized MSE (NMSE) can be minimized.
Likewise, standard deviation (STD) between real and estimated values of the parameter can be discussed and the different DKFs are implemented in Matlab/Simulink code in order to demonstrate the effectiveness of DBEKF estimator compared to the other filter simulation results are satisfying since good agreement between real and estimated parameters was obtained which means an acceptable noise filtering quality of the designed Kalman estimators.
All estimators can be used in on for low scale generator.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Larakeb, M.& Bin Tunisi, A.& Djeghloud, H.. 2016. On-line parameters estimation of low scale SPSG using discrete Kalman Filters. Journal of Electrical Systems،Vol. 12, no. 4, pp.770-785.
https://search.emarefa.net/detail/BIM-739655
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Larakeb, M.…[et al.]. On-line parameters estimation of low scale SPSG using discrete Kalman Filters. Journal of Electrical Systems Vol. 12, no. 4 (2016), pp.770-785.
https://search.emarefa.net/detail/BIM-739655
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Larakeb, M.& Bin Tunisi, A.& Djeghloud, H.. On-line parameters estimation of low scale SPSG using discrete Kalman Filters. Journal of Electrical Systems. 2016. Vol. 12, no. 4, pp.770-785.
https://search.emarefa.net/detail/BIM-739655
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 784-85
رقم السجل
BIM-739655
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
![](/images/ebook-kashef.png)
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
![](/images/kashef-image.png)