2012
DOI: 10.1007/s11708-012-0190-1
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Sensorless direct torque control for salient-pole PMSM based on extended Kalman filter fed by AC/DC/AC converter

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Cited by 12 publications
(4 citation statements)
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“…The general form of the PMSM model in a system with dq coordinates rotating with the rotor can be expressed as follows: The reference model was prepared using Matlab-Simulink environment. Then the C-code was generated, using tools proa possibility to use an observer which estimates the position using any method: using signal injections or the observers, e.g., based on back EMF estimation, using Luenberger and modified Luenberger observers [26], based on various realizations of Kalman filter [27][28] [29][30], using sliding mode observers [31][32] [33] and artificial neural networks [34]. As mentioned above, the control system utilizes the Luenberger observer.…”
Section: The New Control Structurementioning
confidence: 99%
“…The general form of the PMSM model in a system with dq coordinates rotating with the rotor can be expressed as follows: The reference model was prepared using Matlab-Simulink environment. Then the C-code was generated, using tools proa possibility to use an observer which estimates the position using any method: using signal injections or the observers, e.g., based on back EMF estimation, using Luenberger and modified Luenberger observers [26], based on various realizations of Kalman filter [27][28] [29][30], using sliding mode observers [31][32] [33] and artificial neural networks [34]. As mentioned above, the control system utilizes the Luenberger observer.…”
Section: The New Control Structurementioning
confidence: 99%
“…The role of the inverter is to make the stator phases switch, depending on the rotor position so that the PMSMs operate with varying speed. The inverters are acted by using the controllers, but these require rotor speed, rotor position and load torque measurements (El Magri et al, 2010;Benchabane et al, 2012). It is known that mechanical sensor-based solutions are costly and not sufficiently reliable.…”
Section: Introductionmentioning
confidence: 99%
“…The actual investigations are mainly focused on: zero speed range [1][2][3][4], high dynamic performance [5,6], motor supplied through choke or LC filter [7][8][9] and supplied by matrix converter [1,10]. Various approaches to the sensorless control are applied: using signal injections (typical application is zero speed range), based on back EMF estimation -including continuous observer of the kind which is presented in the paper and sliding mode based observers [11], based on Kalman filter [12,13], an adaptive interconnected observer [14] and the use of the artificial neural networks [15,16]. An additional modification that improves the sensorless performance, may be the motor parameter online identification [17] which may improve sensorless performance for low speed range.…”
Section: Introductionmentioning
confidence: 99%