• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.4
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• pp.343-351
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• 2000

This paper introduces a new rotor position estimation algorithm for the Switched Reluctance Motor, based on the magnetizing curves only at aligned and unaligned rotor positions. The flux linkage is calculated by measured data from phase voltage and phase current, and calculated data are used as the input of magnetizing profiles for rotor position detection. The fuzzy flux observer using novel knowledge-based fuzzy controller are presented to achieve sensorless control of the SRM. The method for selecting optimal angle is proposed for the rotor position detection. The robustness of the proposed algorithm is proved through the comparison of the simulation and experimental results.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.2
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• pp.168-175
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• 2009

This paper proposes an enhanced algorithm for sensorless control of 45,000rpm/22kw type Permanent Magnetic Synchronous Motor (PMSM) with air-foil bearing. The proposed algorithm is based on iterative adaptive flux observer for sensorless control of the motor in wide speed range by on-line estimating angle and velocity of rotor. Simulation error between actual and estimated angle of rotor is analyzed to enhance characteristics of frequency response of conventional adaptive flux observer, which results in stable response in wide range of speed. Using the iteration number for stable phase-delay characteristics, the observer enhances the dynamic characteristics of the observer within current control period. The experiment results show the reliable performance of the proposed algorithm through starting to high speed operating range.

• Proceedings of the KIEE Conference
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• 2001.04a
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• pp.277-280
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• 2001

This paper presents a speed sensorless implementation of digital speed control system of Surface Permanent-Magnet Synchronous Motor(SPMSM) drives with a direct torque control(DTC). The system presented are stator flux and torque observer of stator flux feedback control model that inputs are current and voltage sensing of motor terminal with estimated rotor angle for a low speed operating area, two hysteresis band controllers, an optimal switching look-up table, rotor speed estimator, and IGBT voltage source inverter by using fully integrated control software. The developed speed sensorless control system are shown a good motion control response characteristic results and high performance features using 1.0Kw purposed servo drive SPMSM.

• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.109-111
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• 1997

A sensorless drive of induction motor has several advantages; low cost and mechanical simplicity. This paper investigates a field-oriented control method without speed and flux sensors. The control strategy is to design an adaptive state observer for flux estimation and to estimate the rotor speed from the estimated rotor flux and stator current. The entire control algorithm including space vector PWM is implemented by software of the digital signal processor TMS320C31. The experimental results indicate good speed responses.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.397-400
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• 2001

This paper presents a implementation of digital sensorless position control system of surface permanent-magnet synchronous motor (SPMSM) drive with a direct torque control (DTC). The system are stator flux and torque observer of stator flux feedback control model that inputs are current and voltage sensing of motor terminal with estimated rotor angle for a low speed operating area, two hysteresis band controllers, an optimal switching look-up table, rotor speed estimator, and IGBT voltage source inverter by using fully integrated control software. The developed sensorless control system are shown a good motion control response characteristic results and high performance features using 1.0 (kW) purposed servo drive SPMSM.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.366-370
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• 1998

Indirect vector control for induction motors requires the use of observers for estimation or observation of rotor flux magnitude and position. In this paper, authors discribe the induction motor vector control and introduce a nonlinear observer, named ELO(extended Luenberger Observer), without simulation results as a preliminary work for trial application. Normally, design of nonlinear observer need coordinate transfromation and linearization through solving the partial different equation. However, ELO requires minimal solution of nonlinear partial differential equation. Simulation was performed by under the enviroment of Matlab and Simulink without the proposed observer because we are still working. Simulation was performed with conventional flux observer, a dc-ac inverter by SVPWM technique, a vector controller armed with multiple PI controllers

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.4
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• pp.377-383
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• 2002

To obtain a high performance in a direct vector controlled induction machine, it is essential to obtain the current rotor flux. The accuracy of flux observers for induction machines inherently depends on parameter sensitivity. This paper proposes an analysis method for conventional flux observers using "parameter sensitivity". The "parameter sensitivity" is defined as the ratio of the percentage change in the system transfer function to the percentage change of the parameter variation. We define the ratio between real flux and estimated no as the transfer function, and analyze a parameter sensitivity of this transfer function. Practical verification is presented to conform the capabilities of the proposed analysis method.sed analysis method.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.505-508
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• 1999

Conventional adaptive speed estimators cannot avoid the influence of the non-linear inductance variation under the saturation conditions. Without speed sensors, it is difficult to identify the inductance variation using a reactive power mode because the model contains a term of the rotor speed. In this paper, we propose a novel speed estimator having hybrid architecture in order to estimate both the rotor speed and the inductance variation simultaneously when the motor flux is saturated. Proposed estimator consists of the error between the flux obtained from the stator voltage equation and the flux estimated from the rotor flux observer. Introducing a new correction term into the estimator increases the estimation ability of the conventional speed estimator even though the motor flux is saturated. The convergence of the speed estimation error is examined by simulation Furthermore, the experimental results show the validity of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.3
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• pp.173-179
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• 2004

A synthesis method of the reduced-order extended Luenberger observer (ROELO) and its design procedure for a nonlinear dynamic system are presented. This paper proposes a method to reduce the order of the observer and to ! elect the observer gain matrix. The proposed algorithm is applied for high performance induction motor drives without a speed sensor The simulation and experiment results show that the proposed ROELO provides both rotor flux and rotor speed estimation with good performance.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.160-164
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• 2007

MRAS observer, which is based on adaptive control theory, estimates speed and position by using optimal observer gains on the basis of Lyapunov stability theory. However, in case of MRAS theory, position estimation error is in existence because of non-linearity for inductance variation and limit cycles for position estimation. The adaptive sliding observer based on the variable structure control theory estimates the speed and position for zero of estimation error by using the sliding surface equal to the error between speed and position estimation. The binary observer estimates the rotor speed and rotor flux with alleviation of the high-frequency chattering, and retains the benefits achieved in the conventional sliding observer, such as robustness to parameter and disturbance variations. The speed and position sensorless control of SRM under the load and inductance variation is verified by the experimental results.