• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.3
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• pp.125-132
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• 2002

PMSMS (permanent magnet synchronous motors) are widely used in industrial applications and home appliances because of their high torque to inertia ratio, superior power density, and high efficiency. For high performance control, accurate informations about the rotor position is essential. Sensorless algorithms have lately been studied extensively due to the high cost of position sensors and their low reliability in harsh environments. A novel position sensorless speed control for PMSMs uses indirect flux estimation and is presented in this paper. Rotor position and angular velocity are estimated by the proposed indirect flux estimation. Linkage flux and magnetic field flux are calculated by the voltage equations and the measured phase current without any integration. Instead of linkage flux calculation with integral operation, indirect flux and differential magnetic field are used for the estimation of rotor position. A proper rejection technique fur current noise effect in the calculation of differential linkage flux is introduced. The proposed indirect flux detecting method is free from the integral rounding error and linkage flux drift problem, because differential linkage flux can be calculated without any integral operation. Furthermore, electrical parameters of the PMSM can be measured by the proposed TCM (time compression method) for soft starting and precise estimation of rotor position. The position estimator uses accurate electrical parameters that are obtained from the proposed TCM at starting strategy. In the operating region, a proper compensation method fur temperature effect can compensate fir the estimation error from the variation of electrical parameters. The proposed novel position sensorless speed control scheme is verified by the experimental results.

• 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.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.192-195
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• 2002

The thesis proposes the sensorless vector control method that estimates the rotor speed and rotor time constant at the same time using stator current. In the proposed method, stator current error in the stationary reference frame is proportional to estimated speed error, and stator current error in the synchronous reference frame is proportional to estimated rotor time constant error. The proposed method can simultaneously produce a fast speed estimation and rotor time constant estimation. Therefore, this new method offers an improvement in the performance of a sensorless vector controller. And, the superiority of the proposed method is verified by simulation.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.2
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• pp.101-109
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• 2005

The newly developed speed sensorless control scheme is proposed to estimate both motor speed and rotor resistance simultaneously using variable rotor flux. The rotor flux is given as sinusoidal waveform with an amplitude and a frequency without affecting precise torque control. Especially the proposed method makes the simultaneous estimation of rotor resistance and speed with high precision even though at the low speed area including a few rpm. Moreover, on-line identification of rotor resistance can be performed simply without calculating troublesome trigonometric functions and complicated integral computation. Therefore, the proposed system can be accomplished by using very cheap microprocessors for several applications. The results of the numerical simulations and experiments demonstrate that this method is effective to estimate the speed and on-line identification of rotor resistance for sensorless induction motors.

• 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.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1123-1125
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• 2000

This paper presents the speed estimation using ANN and the rotor parameter Identification based on the MRAS theory for the sensorless induction motor drives. The motor speed is estimated using ANN model which contains the rotor parameter. And the rotor parameter is identified using MRAS scheme which contains the rotor speed. The rotor speed estimate converges to its actual value as the rotor parameter error converges toward the zero. The simulation using Matlab/Simulink is performed to verify the effectiveness of the proposed scheme.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.326-331
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• 1990

In the vector-controlled induction machine drive, mechanical sensors restrict the wide applications of high performance AC drives. So in resent years, many papers have been presented which doesn't need mechanical sensors, named by sensorless vector control. But sensorless control has a few serious problem, one of which Is poor speed estimation in case of incorrect rotor resistance (Rr) information. This paper describes the stator flux orientation speed control strategy with the speed estimation algorithm. and the method of adapting Rr change due to thermal heating. By proposed method. We can acquire precise speed estimation and higher 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.

• Journal of Power Electronics
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• v.9 no.4
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• pp.654-666
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• 2009

Direct torque control (DTC) of induction machines (IM) is a well-known strategy of these drives control which has a fast dynamic and a good tracking response. In this paper a nonlinear DTC of speed sensorless IM drives is presented which is based on input-output feedback linearization control theory. The IM model includes iron losses using a speed dependent shunt resistance which is determined through some effective experiments. A stator flux vector is estimated through a simple integrator based on stator voltage equations in the stationary frame. A novel method is introduced for DC offset compensation which is a major problem of AC machines, especially at low speeds. Rotor speed is also determined using a rotor flux sliding-mode (SM) observer which is capable of rotor flux space vector and rotor speed simultaneous estimation. In addition, stator and rotor resistances are estimated using a simple but effective recursive least squares (RLS) method combined with the so-called SM observer. The proposed control idea is experimentally implemented in real time using a FPGA board synchronized with a personal computer (PC). Simulation and experimental results are presented to show the capability and validity of the proposed control method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.4
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• pp.199-205
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• 2012

This paper propose a improved parameter estimations of five-phase squirrel-cage induction motor(IM) for speed control system on field oriented control(FOC). In order to high performance control of ac the motors using a FOC and DTC(direct torque control) algorithm, there are required precise motor parameters for slip calculation, flux observer, controller gain, rotor position and speed estimation, and so on. We are suggest a estimation method of the motor parameters that developing five-phase squirrel-cage IM have a stator of concentrated winding for experimental. There are results of stator winding test, no-load test, locked rotor test, and obtained equivalent circuits using manufactured experimental apparatus. For presenting the superior performance of the speed control system in adapted the parameters, experimental results are presented using a 32-bit fixed point TMS320F2812 DSP with 1.5[KW] IM.