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Sensorless Control of Synchronous Reluctance Motor Drives Based on the TLS EXIN Neuron
- Source :
- International Electric Machines & Drives Conference, International Electric Machines & Drives Conference, May 2019, San Diego, CA, United States
- Publication Year :
- 2019
- Publisher :
- HAL CCSD, 2019.
-
Abstract
- International audience; This paper proposes a rotor speed and position estimation scheme for the synchronous reluctance motor (SynRM) drive system based on its active flux model in the stator reference frame and the total least squares (TLS) EXIN neuron. Firstly, the active flux model of the SynRM in the stator reference frame is reconstructed to the overdetermined matrix equations. On the basis of that, the estimation of the rotor speed of the SynRM is transferred into solving a TLS problem. The TLS EXIN neuron, which is a recursive TLS algorithm, is used to solve this problem online to extract the rotor speed. The estimated rotor position is obtained from the estimated rotor speed based on the integrator. The feasibility and effectiveness of the proposed rotor speed estimation scheme have been verified by the simulation results.
- Subjects :
- 0209 industrial biotechnology
Computer science
Stator
Rotor (electric)
020208 electrical & electronic engineering
[SPI.NRJ]Engineering Sciences [physics]/Electric power
02 engineering and technology
law.invention
[SPI.AUTO]Engineering Sciences [physics]/Automatic
Overdetermined system
Matrix (mathematics)
020901 industrial engineering & automation
Control theory
law
Position (vector)
Integrator
0202 electrical engineering, electronic engineering, information engineering
[PHYS.MECA.THER]Physics [physics]/Mechanics [physics]/Thermics [physics.class-ph]
[PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph]
Total least squares
Reference frame
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- International Electric Machines & Drives Conference, International Electric Machines & Drives Conference, May 2019, San Diego, CA, United States
- Accession number :
- edsair.doi.dedup.....ad08de99672be75d295e4c7184440f7f