Please use this identifier to cite or link to this item: doi:10.22028/D291-30608
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Title: Robust Load-Torque Estimation for DC Motor without Torque Sensor
Author(s): Fabbri, Stefano
Nienhaus, Matthias
Grasso, Emanuele
Language: English
Title: 2019 AEIT International Annual Conference (AEIT)
Startpage: 1
Endpage: 6
Publisher/Platform: IEEE
Year of Publication: 2019
Title of the Conference: AEIT 2019
Place of the conference: Florence, Italy
Publikation type: Conference Paper
Abstract: External load-torque estimation for electrical motor is important in order to improve control performance as well as obtaining information about interaction with the environment. This paper presents a performance and robustness comparison among three different types of algorithms for the estimation of the external load-torque for low-power DC motors. The Kalman filter is presented as the standard estimation technique and it is compared to the H∞filter and the Super-Twisting Sliding Mode Observer (STSMO). The algorithms are based on the position and speed measurements of the rotor.
DOI of the first publication: 10.23919/AEIT.2019.8893289
URL of the first publication:
Link to this record: hdl:20.500.11880/28941
ISBN: 978-8-8872-3745-0
Date of registration: 3-Apr-2020
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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