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http://hdl.handle.net/11375/31217Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Zhang W | - |
| dc.contributor.author | Gadsden SA | - |
| dc.contributor.author | Habibi SR | - |
| dc.date.accessioned | 2025-02-27T20:07:19Z | - |
| dc.date.available | 2025-02-27T20:07:19Z | - |
| dc.date.issued | 2013-09-11 | - |
| dc.identifier.issn | 0743-1619 | - |
| dc.identifier.issn | 2378-5861 | - |
| dc.identifier.uri | http://hdl.handle.net/11375/31217 | - |
| dc.description.abstract | Estimation of stator winding resistance in brushless DC motors is important for fault detection and diagnosis. The most popular linear estimation method to date remains the Kalman filter (KF), and the extended form (EKF) for nonlinear systems and measurements. However, a relatively new method referred to as the smooth variable structure filter (SVSF) was introduced in an effort to overcome some of the instability issues with the KF. Further to this development, a new nonlinear estimation strategy was created based on combining elements of the EKF with the SVSF. This new method, referred to as the EK-SVSF, has been applied to a brushless DC motor for estimating the stator winding values. The results are compared with the popular EKF. © 2013 AACC American Automatic Control Council. | - |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | - |
| dc.subject | 40 Engineering | - |
| dc.subject | 4008 Electrical Engineering | - |
| dc.subject | 4009 Electronics, Sensors and Digital Hardware | - |
| dc.title | Nonlinear estimation of stator winding resistance in a brushless DC motor | - |
| dc.type | Article | - |
| dc.date.updated | 2025-02-27T20:07:19Z | - |
| dc.contributor.department | Mechanical Engineering | - |
| dc.identifier.doi | https://doi.org/10.1109/acc.2013.6580564 | - |
| Appears in Collections: | Mechanical Engineering Publications | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 031-gadsden_conf_031.pdf | Published version | 729.51 kB | Adobe PDF | View/Open |
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