• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.163-165
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• 2006

This paper presents a implementation of speed sensorless vector control algorithm of induction motor using MATLAB/SIMULINK amd dSPACE DSl104 R&D board. The estimation of rotor flux linkage and rotor speed is carried out using model reference adaptive system(MRAS) method. Estimated rotor speed is used to speed controller of induction motor. Simulation results are presented to confirm speed sensorless vector control algorithm.

• Journal of Power Electronics
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• v.6 no.3
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• pp.235-244
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• 2006

Recently, speed sensorless vector control for synchronous reluctance motors (SYRMs) has deserved attention because of its advantages. Although rotor angle calculation using flux estimation is a straightforward approach, the DC offset can cause an increasing pure integrator error in this estimator. In addition, this method is affected by parameter fluctuation. In this paper, to control the motor at the low speed region, a modified programmable cascaded low pass filter (MPCPLF) with sensorless online parameter identification based on a block pulse function is proposed. The use of the MPCLPF is suggested because in programmable, cascade low pass filters (PCLPF), which previously have been applied to induction motors, the drift increases vastly wl)en motor speed decreases. Parameter identification is also used because it does not depend on estimation accuracy and can solve parameter fluctuation effects. Thus, sensorless speed control in the low speed region is possible. The experimental system includes a PC-based control with real time Linux and an ALTERA Complex Programmable Logic Device (CPLD), to acquire data from sensors and to send commands to the system. The experimental results show the proposed method performs well, speed and angle estimation are correct. Also, parameter identification and sensorless vector control are achieved at low speed, as well as, as at high speed.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.2
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• pp.185-191
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• 2004

This study describes the scheme of vector drive system without speed sensor for AC servo motor using theory of a flux observer and based on the field oriented vector control. The new method of speed estimation is presented from operate with the position and magnitude of the secondary flux which obtain from the voltage reference and detected current. As the estimated speed is settled by the flux and the machine-specific parameters. this method don't need to adjust the gain of the parameter. Based on the derived theory for vector control. the scheme for sensorless vector drive of AC servo motor is designed and realized. And the experiment verifies it passable to realize the sensorless vector drive based on a field-oriented type.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.873-881
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• 2014

Speed sensorless modes of operation are becoming standard solution in the area of electric drives. This paper presents flux estimator and speed estimator for the speed sensorless vector control of induction motors. The proposed sensorless methods are based on the model reference adaptive system (MRAS) observer and adaptive speed observer (ASO). The proposed speed estimation algorithm can be employed in the power control of grid connected induction generator for wind power applications. Two proposed schemes are verified through computer simulation PSIM and compared their simulation results.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.540-543
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• 1999

This paper describes a speed sensorless algorithm for vector control system with compensated stator resistance and rotor time constant of induction motor using a model reference adaptive system(MRAS). The system are composed of two MRAC, one is a rotor speed estimation and a stator resistor identification by back-EMF observer, other is used to identify rotor time constant by magnetizing current observer, so that the estimation can be cover a very low speed range with a robust control. The suggest control strategy and estimation method have been validated by simulation study. In the simulation using Matlab/Simulik, the proposed speed sensorless vector control system are shown to operate very well in spite of variable rotor time constant and load fluctuation.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1086-1087
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• 2007

This paper presents a implementation of speed sensorless vector control algorithm of induction motor using MATLAB/SIMULINK. The proposed method utilize the combination of the voltage model based on stator equivalent model and the current model based on rotor equivalent model, which enables stable estimation of rotor flux. Estimated rotor speed, which is used to speed controller of induction motor, is based on estimated flux. The overall system consisted of speed controller with the most general PI controller, current controller, flux controller. Speed sensorless vector control algorithm is implemeted as block diagrams using MATLAB/SIMULINK. Realtime control is perform by dSPACE DS1104 control board and Real-Time-Interface(RTI).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.12
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• pp.82-87
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• 2011

In this paper, a sensorless speed control system is designed for the next generation high speed railway at zero and low speed region. The applied vector control scheme is a maximum torque per ampere(MTPA) method to utilize reluctance torque of IPMSM. The designed sensorless control scheme is a rotating high frequency voltage signal injection method. To verify the designed system, a simulator for the vector controller and sensorless controller is implemented using Matlab/simulink.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.1
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• pp.100-107
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• 2003

This study was to control magnetic field orientation-typed sensorless vector control by applying the theory of a rotor flux observer to drive an induction motor. This research suggested a new speed estimation method that estimates speed with the rotor flux obtained by using a flux observer and the variable of state current detected by a current sensor without a speed sensor. Because the speed estimation method is independent from the motor constants, it is not necessary to control the gain of the parameters and the algorithm is simple. In the findings of the study, the researcher was convinced of the control function and the possibility of realization in the simulation experiment of sensorless vector control system by using DSP(Digital Signal Prosessor).

• Journal of Power System Engineering
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• v.18 no.5
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• pp.129-136
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• 2014

This paper proposes improvement on sensorless vector control performance of a permanent magnet synchronous motor (PMSM) with sliding mode observer. An adaptive observer gain and second order cascade low-pass filter (LPF) were used to improve the estimation accuracy of the rotor position and speed. The adaptive observer gain was applied to suppress the chattering intensity and obtained by using the Lyapunov's stability criterion. The second order cascade LPF was designed for the system to escalate the filtering performance of the back-emf estimation. Furthermore, genetic algorithm was used to optimize the system PI controller's performance. Simulation results showed the effectiveness of the suggested improvement strategy. Moreover, the strategy was useful for the sensorless vector control of PMSM to operate on the low-speed area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2625-2632
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• 2009

Recently, a speed control method of induction motor by vector control theory is applied to highly efficient industrial field. The speed sensors attached to motor are used for detection of rotating speed. In the case using speed sensor, the installation of cable for minimization of electric noise, weaken maintenance, increase of price are demerit. Therefore the study of speed sensorless vector control theory performed activity. The design of sensorless vector controller for induction motor using tabu search is studied. The proposed sensorless vector control for Induction Motor is composed of two parts. The first part is for optimizing the speed estimation with initial PI parameters. The second part is for optimizing the speed control with initial PI parameters using tabu search. Proposed tabu search is improved by neighbor solution creation using Triangular random distribution. In order to show the usefulness of the proposed method, we apply the proposed controller to the sensorless speed control of an actual AC induction Motor System. The performance of this approach is verified through simulation and the experiment.