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doi:10.22028/D291-29544
Title: | A Sliding Mode Observer for Sensorless Operation of Low Power PMS Machines |
Author(s): | Fabbri, Stefano Grasso, Emanuele König, Niklas Nienhaus, Matthias |
Language: | English |
Title: | 2018 AEIT International Annual Conference |
Startpage: | 1 |
Endpage: | 6 |
Publisher/Platform: | IEEE |
Year of Publication: | 2018 |
Title of the Conference: | AEIT 2018 |
Place of the conference: | Bari, Italy |
Publikation type: | Conference Paper |
Abstract: | The Sliding Mode Observer (SMO) is a non-linear estimation method that is acknowledged to be robust against parameter variations and noise that persist over a control system. In this work, the comparison of three different implementations of the SMO is examined in the case of the estimation of the back electromagnetic force (BEMF) of a permanent magnet synchronous motor (PMSM). In particular, the classical signum function of a SMO is compared to a saturated linear function with steep slope and to a sigmoidal function. These functions are chosen in order to reduce the typical chattering phenomenon. Moreover, performance of the implemented solutions is discussed in terms of maximum achievable speed and current consumption. The tests are carried out using a PIC32MZ microcontroller and a PMSM with surface mounted magnets. |
DOI of the first publication: | 10.23919/AEIT.2018.8577402 |
URL of the first publication: | https://ieeexplore.ieee.org/document/8577402 |
Link to this record: | hdl:20.500.11880/28335 http://dx.doi.org/10.22028/D291-29544 |
ISBN: | 978-88-87237-40-5 978-88-87237-42-9 |
Date of registration: | 21-Nov-2019 |
Faculty: | NT - Naturwissenschaftlich- Technische Fakultät |
Department: | NT - Systems Engineering |
Professorship: | NT - Prof. Dr. Matthias Nienhaus |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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