Dual Kalman Filters Analysis for Interior Permanent Magnet Synchronous Motors
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Authors
This paper deals with an analysis and design of Dual Extended Kalman Filters (DKFs) to estimate parameters and state variables in Permanent Magnet Synchronous Machines (PMSMs) to be utilized in a control structure. A dual estimation problem consists of a simultaneous estimation of states of the dynamical system and its parameters using only noisy output observations. In this paper, the limit of an Augmented and Extended Kalman Filter (AEKF) obtained through standard state augmentation to estimate parameters is shown and, alternatively, a DKF approach which is characterized by the use of the state model descriptions in the output of an AEKF is proposed. The two different approaches are analyzed and compared. These results are supported by simulations.
| Original language | English |
|---|---|
| Title of host publication | Advanced, Contemporary Control : Proceedings of KKA 2020—The 20th Polish Control Conference, Łódź, Poland, 2020 |
| Editors | Andrzej Bartoszewicz, Jacek Kabziński, Janusz Kacprzyk |
| Number of pages | 12 |
| Volume | 1 |
| Place of Publication | Cham |
| Publisher | Springer Verlag |
| Publication date | 01.01.2020 |
| Pages | 424-435 |
| ISBN (print) | 978-3-030-50935-4 |
| ISBN (electronic) | 978-3-030-50936-1 |
| DOIs | |
| Publication status | Published - 01.01.2020 |
| Event | 20th Polish Control Conference, PCC 2020 - Lodz University of Technology, Lodz, Poland Duration: 22.06.2020 → 24.06.2020 Conference number: 20 https://www.kka.p.lodz.pl/index_e.php |
- Augmented Extended Kalman Filter, Dual Extended Kalman Filter, Parameters estimation, Permanent Magnet Synchronous Machine
- Engineering