• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.10 no.3
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• pp.55-63
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• 1996

In this paper, a vector control system is implemented to drive CRPWM inverter fed induction motor. The rotor flux is estimated using the rotor coordinates flux model and the stator coordinates ramp comparison controller is used as a current controller. The microcontroller 80C196 is used for the computation of the estimation of the rotor flux, the speed controller, the flux controller, the vector rotation, and the phase transformation The current controller is implemented using the analog circuit in order to reduce the burden of the microcontroller. For the proposed system, the digital simulation is performed to examine the feasibility and the superior characteristics of the current controller and the system transient response is verified through the experiment.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.1
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• pp.37-46
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• 2004

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 method, 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 estimation error is unclear. 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. The robustness of the rotor flux-based MRAC, back EMF-based MRAC, and proposed MRAC is compared based on a sensitivity function about each error of stator resistance, rotor time constant, mutual inductance. Consequently, the proposed method is much more robust than the conventional methods as regards errors in the mutual inductance, stator resistance. Therefore, the proposed method offers a considerable improvement in the performance of a sensorless vector controller at a low speed. In addition, the superiority of the proposed method and the validity of sensitivity functions were verified by simulation and experiment.

• Proceedings of the KIPE Conference
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• 2004.07b
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• pp.972-975
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• 2004

This paper presents a simulation results of sensorless control of Switched Reluctance Motor(SRM) using neural network. The basic algorithm of this scheme is based on the flux linkage characteristic according to the phase current and the rotor position. A sufficient simulation data was used for neural network training. Through measurement of the phase flux linkage and phase currents the neural network is able to estimate the rotor position. The simulation result shows some good results, and possibility of this algorithm.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.200-204
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• 2002

When the vector control, which does not need a speed? signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. This paper describes a rotor speed identification method of induction motor based on the theory of flux model reference adaptive system. The estimator execute the rotor speed identification so that the vector control of the induction motor may be achieved. The improved auxiliary variable of the two model are introduced to perform accurate rotor speed estimation. Simulation result show the validity of the proposed control method.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1276-1278
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• 2005

In this paper, we propose an adaptive sliding mode observer-based control of induction motors with uncertainties. The proposed adaptive sliding mode flux observer generates estimates both for the unknown parameters(load torque and rotor resistance) and for the unmeasured state variable (rotor fluxes); they converge to the corresponding true value under persistency of excitation which actually holds in typical operating conditions. The proposed controller guarantees speed tracking and bounded signals for every initial condition of the motor. Simulations show that all estimation errors tend quickly to zero so that high tracking performances are achieved both for speed and rotor flux.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2001.11a
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• pp.181-185
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• 2001

This paper presents a digitally speed sensorless control system for induction motor with direct torque control (DTC). The drive is based on Mode1 Reference Adaptive System (MRAS) using state observer as a reference model fat flux estimation. The system are closed loop stator flux and torque observer for wide speed range that inputs are currents and voltages sensing of motor terminal, model reference adaptive control (MRAS) with rotor flux linkages for the speed turning aignal at low speed range, two hysteresis controllers. The Proposed system is verified through simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.9
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• pp.1269-1274
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• 2012

In this paper, the iron loss was calculated using estimated iron loss coefficient at 650W Interior Permanent Magnet Synchronous Motor(IPMSM) and 250W IPMSM. The iron loss coefficients was estimated different according to electrical steel material used to stator and rotor core in motor. Aspect of The rotating flux field and alternating flux field was confirmed by magnetic field behavior and harmonic analysis in stator core, the iron loss was calculated using flux density by Finite Element Method(FEM) and estimated coefficients by iron loss coefficient estimation proposed in this paper. The iron loss experiment was performed for verified to iron loss calculation, and the iron loss coefficients were verified by comparison of iron loss calculation value and experimental value.

• 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 KIEE Conference
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• 2007.07a
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• pp.1650-1651
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• 2007

This paper presents a novel nonlinear speed control strategy for induction motor utilizing exact feedback linearization with states feedback. The speed and flux control loops utilize nonlinear feedback which eliminates the need for tuning, while ordinary proportional-integral controllers are used to control the stator current of d-axis the speed. The control scheme is derived in rotor field coordinates and employs an appropriate estimator for estimation of the rotor flux angle, flux magnitude.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.488-492
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• 2004

In this paper, the design of a speed sensorless vector control system for induction motor is performed by using a new sliding mode technique based on current model flux observer. A current and flux observer based on the current estimation error is constructed. The proposed current observer includes a sliding mode function, which is derivative of the flux. That is, sliding mode observer which allows the estimation of both the rotor speed and flux based on the measurement of motor terminal quantities, would be proposed. And, a synergetic speed controller using the estimated speed signal is designed to stabilize the speed loop. Simulation results are presented to confirm the theoretical analysis, and to show the system performance with different observer gains and the influence of the motor parameter.