Name
Title | ||
|---|---|---|
A critical evaluation and experimental verification of Extended Kalman Filter, Unscented Kalman Filter and Neural State Filter for state estimation of three phase induction motor |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.asoc.2010.12.022 | Appl. Soft Comput. |
Keywords | Field | DocType |
relative performance,simulation result,experimental data,experimental verification,ekf,extended kalman filter,conditions ekf estimate,ukf,induction motor,nsf performance,extensive simulation study,critical evaluation,state estimation,nsf estimate,neural state filter,unscented kalman filter,nsf,operant conditioning | Induction motor,Alpha beta filter,Extended Kalman filter,Fast Kalman filter,Control theory,Unscented transform,Kalman filter,Invariant extended Kalman filter,Ensemble Kalman filter,Mathematics | Journal |
Volume | Issue | ISSN |
11 | 3 | Applied Soft Computing Journal |
Citations | PageRank | References |
4 | 0.46 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| P. Senthil Kumar | 1 | 114 | 8.64 |
| J. Prakash | 2 | 10 | 3.91 |
| P. Kanagasabapathy | 3 | 6 | 1.87 |