Dual Kalman Filters Analysis for Interior Permanent Magnet Synchronous Motors

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-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 languageEnglish
Title of host publicationAdvanced, Contemporary Control : Proceedings of KKA 2020—The 20th Polish Control Conference, Łódź, Poland, 2020
EditorsAndrzej Bartoszewicz, Jacek Kabziński, Janusz Kacprzyk
Number of pages12
Volume1
Place of PublicationCham
PublisherSpringer
Publication date01.01.2020
Pages424-435
ISBN (print)978-3-030-50935-4
ISBN (electronic)978-3-030-50936-1
DOIs
Publication statusPublished - 01.01.2020
Event20th Polish Control Conference, PCC 2020 - Lodz University of Technology, Lodz, Poland
Duration: 22.06.202024.06.2020
Conference number: 20
https://www.kka.p.lodz.pl/index_e.php

    Research areas

  • Augmented Extended Kalman Filter, Dual Extended Kalman Filter, Parameters estimation, Permanent Magnet Synchronous Machine
  • Engineering