کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
496753 | 862869 | 2011 | 10 صفحه PDF | دانلود رایگان |
This paper deals with the design and implementation of Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Neural State Filter (NSF) for the state estimation of a three-phase induction motor. Extensive simulation studies have been carried out to assess the relative performance of the three filters under various machine operating conditions and model uncertainties. Filter performance for similar conditions was verified with experimental data and found to be consistent with simulation results. The simulation and experimental results indicate that for most conditions EKF estimates are better than UKF while error in NSF estimates is large. However NSF performance is relatively better than other two filters for specific condition like large parameter uncertainty.
Journal: Applied Soft Computing - Volume 11, Issue 3, April 2011, Pages 3199–3208