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Urasaki Naomitsu,Senjyu Tomonobu,Funabashi Toshihisa,Sekine Hideomi The Korean Institute of Power Electronics 2006 JOURNAL OF POWER ELECTRONICS Vol.6 No.4
This paper presents a neural network based adaptive dead-time compensation strategy for an inverter fed permanent magnet synchronous motor drive. The neural network is used for identifying the dead-time compensation time (DTCT) that includes an equivalent dead-time, turn-on/off time and on-state voltage components of the voltage source inverter. In order to train the neural network, desired DTCTs for eight operating points are prepared as training data. The trained neural network can identify a desired DTCT for any operating point because it has the capability of the interpolation. The accuracy of the identified DTCT is experimentally confirmed by comparing the calculated active power with a measured one.
Urasaki, Naomitsu,Senjyu, Tomonobu,Uezato, Katsumi The Korean Institute of Power Electronics 2003 JOURNAL OF POWER ELECTRONICS Vol.3 No.1
This paper presents parameter measurement for permanent magnet synchronous motors based on the P-Q circle diagram. Three electrical parameters of permanent magnet synchronous motors, i.e., the equivalent iron loss resistance, armature inductance, and electrical motive force (emf) coefficient are simultaneously measured. The advantages of this method are that it can be implemented under constant excitation and it dispenses with the generating test for the emf coefficient. The proposed method is applied to a 160w permanent magnet synchronous motor, and then the measurement results are analyzed.
High Efficiency Drive Technique for Synchronous Reluctance Motors Using a Neural Network
Naomitsu Urasaki,Tomonobu Senjyu 전력전자학회 2006 JOURNAL OF POWER ELECTRONICS Vol.6 No.4
A high efficiency drive technique for synchronous reluctance motors (SynRM) using a neural network (NN) is presented in this paper. High efficiency drive condition depends on the mathematical model of SynRM. A NN is employed as an adaptive model of SynRM. The proposed high efficiency drive technique does not require an accurate mathematical model of SynRM. Moreover, the proposed method shows robustness against machine parameter variations because the training algorithm of the NN is executed on-line. The usefulness of the proposed method is confirmed through experimentation.
Naomitsu Urasaki,Tomonobu Senjyu,Toshihisa Funabashi,Hideomi Sekine 전력전자학회 2006 JOURNAL OF POWER ELECTRONICS Vol.6 No.4
This paper presents a neural network based adaptive dead-time compensation strategy for an inverter fed permanent magnet synchronous motor drive. The neural network is used for identifying the dead-time compensation time (DTCT) that includes an equivalent dead-time, turn-on/off time and on-state voltage components of the voltage source inverter. In order to train the neural network, desired DTCTs for eight operating points are prepared as training data. The trained neural network can identify a desired DTCT for any operating point because it has the capability of the interpolation. The accuracy of the identified DTCT is experimentally confirmed by comparing the calculated active power with a measured one.
Self-Commissioning for Surface-Mounted Permanent Magnet Synchronous Motors
Urasaki, Naomitsu,Senjyu, Tomonobu,Uezato, Katsumi The Korean Institute of Power Electronics 2003 JOURNAL OF POWER ELECTRONICS Vol.3 No.1
This paper presents the self-commissioning for surface-mounted permanent magnet synchronous motor. The proposed strategy executes three tests with a vector controlled inverter drive system. To do this, synchronous d-q axes currents are appropriately controlled for each test. From the three tests, armature resistance, armature inductance, equivalent iron loss resistance, and emf coefficient are identified automatically. The validity of the proposed strategy is confirmed by experimental results.
Self-Commissioning for Surface-Mounted Permanent Magnet Synchronous Motors
Naomitsu Urasaki,Tomonobu Senjyu,Katsumi Uezato 전력전자학회 2003 JOURNAL OF POWER ELECTRONICS Vol.3 No.1
This paper presents the self-commissioning for surface-mounted permanent magnet synchronous motor. The proposed strategy executes three tests with a vector controlled inverter drive system To do this, synchronous d-q axes currents are appropriately controlled for each test. From the three tests, armature resistance, armature inductance, equivalent iron loss resistance, and emf coefficient are identified automatically. The validity of the proposed strategy is confirmed by experimental results.<br/>
Self-Commissioning for Surface-Mounted Permanent Magnet Synchronous Motors
Naomitsu Urasaki,Tomonobu Senjyu,Katsumi Uezato 전력전자학회 2001 ICPE(ISPE)논문집 Vol.2001 No.10
This paper presents the self-commissioning for surface-mounted permanent magnet synchronous motor The proposed strategy executes three tests with a standard inverter drive system To do this, synchronous d-q axes cur-lents are appropriately controlled for each test From the three tests, armature resistance, armature inductance, e-qutvalent iron loss resistance, and emf coefficient are identified automatically The validity of the proposed strategy is confirmed by experimental results.
Naomitsu Urasaki,Tomonobu Senjyu,Katsumi Uezato 전력전자학회 2003 JOURNAL OF POWER ELECTRONICS Vol.3 No.1
This paper presents parameter measurement for permanent magnet synchronous motors based on the P-Q circle diagram.<br/> Three electrical parameters of permanent magnet synchronous motors, ie , the equivalent iron loss resistance, armature inductance, and electrical motive force (emf) coefficient are simultaneously measured The advantages of this method are that it can be implemented under constant excitation and it dispenses with the generating test for the emf coefficient The proposed method is applied to a 160W permanent magnet synchronous motor, and then the measurement results are analyzed<br/>
High Efficiency Drive Technique for Synchronous Reluctance Motors Using a Neural Network
Urasaki Naomitsu,Senjyu Tomonobu The Korean Institute of Power Electronics 2006 JOURNAL OF POWER ELECTRONICS Vol.6 No.4
A high efficiency drive technique for synchronous reluctance motors (SynRM) using a neural network (NN) is presented in this paper. High efficiency drive condition depends on the mathematical model of SynRM. A NN is employed as an adaptive model of SynRM. The proposed high efficiency drive technique does not require an accurate mathematical model of SynRM. Moreover, the proposed method shows robustness against machine parameter variations because the training algorithm of the NN is executed on-line. The usefulness of the proposed method is confirmed through experimentation.
Position Sensorless Control for Ultrasonic Motors Based on Input Voltage Information
Tomonobu Senjyu,Tomohiro Yoshida,Naomitsu Urasaki,Katsumi Uezato,Toshihisa Funabashi,Hideomi Sekine,S. K. Panda 전력전자학회 2004 ICPE(ISPE)논문집 Vol.- No.-
This paper presents a method of position sensorless control of ultrasonic motor (USM). The rotor position of USM is estimated based on the input voltage information. The characteristic of input voltage versus rotor position is expressed by a quadratic function. Since the parameters of quadratic function are adjusted by using recursively least square method, estimated rotor position agrees well with actual rotor position against load torque and motor temperature changes. Position sensorless control is achieved by using estimated rotor position instead of measured rotor position. The validity of the proposed method is confirmed by experimental results.