• 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 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 Institute of Control, Robotics and Systems
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• v.9 no.9
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• pp.692-699
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• 2003

A novel rotor speed estimation method using Model Reference Adaptive Control(MRAC) is proposed to improve the performance of a sensorless vector controller. In the proposed mettled, the stator current is used as the model variable for estimating the speed. In conventional MRAC methods, the relation between the two model errors and the speed estmation error is unclear. Yet, in the proposed method, the stator current error is represented as a function of the first degree for the error value in the speed estimation. Therefore, the proposed method can produce a fast speed estimation and is robust to the parameters error In addition, the proposed method of offers a considerable improvement in the performance of a sensorless vector controller at a low speed. The superiority of the proposed method is verified by simulation and experiment in a low speed region and at a zero-speed.

• Journal of Power Electronics
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• v.5 no.1
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• pp.11-19
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• 2005

This paper describes the two control techniques to perform the sensorless vector control of a PMSM by injecting the high frequency voltage to the stator terminal. The first technique is the estimation algorithm of the initial rotor position. A PMSM possesses the saliency which produces the ellipse of the stator current when the high frequency voltage is injected into the motor terminal. The major axis angle of the current ellipse gives the rotor position information at a standstill. The second control technique is a sensorless control algorithm that injects the high frequency voltage to the stator terminal in order to estimate the rotor position and speed. The rotor position and speed for sensorless vector control is calculated by appropriate signal processing to extract the position information from the stator current at low speeds or standstill. The proposed sensorless algorithm using the double-band hysteresis controller exhibits excellent reference tracking and increased robustness. Experimental results are presented to verify the feasibility of the proposed control schemes. Speed, position estimation and vector control were carried out on the floating point processor TMS320VC33.

• 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 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.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.3
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• pp.126-131
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• 2002

This paper is proposed to position and speed control of interior permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. The rotor position, which is an essential component of any vector control schemes, is calculated through the instantaneous stator flux position and an estimated flux value of rotating reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The validity of the proposed sensorless scheme is confirmed by simulation and its dynamic performance is examined in detail.

• 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).

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.171-175
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• 1998

This paper proposes a speed sensorless vector control of induction motor using a minimum-order EKF(extended kalman filter). Minimum-order EKF has the advantage of reducing the computational estimation cost because the stator current is not estimated. EKF does not deteriorate the performance of the overall speed control system, even though the measurements are relatively noisy. The estimated rotor speed is used for vector control and overall speed control. Computer simulations of the speed sensorless vector control are carried out to test the usefulness of the minimum-order EKF algorithm.