• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.11
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• pp.37-46
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• 1993

Recently, the elimination of speed sensors has been one of the important requirement in vector control systems, because the speed sensor spoil the ruggedness and simplicity of induction motor. This paper proposes sensorless vector control for high performance of induction motor. The proposed vector control scheme is based on a rotor flux and speed which are calculated from the stator voltage and currents with improved flux estimator. The characteristics of vector control employing stator voltage and current generally deteriorate as the speed gets lower acause the calculated rotor flux depends on the stator resistance and it is difficult to calculate rotor flux at low speed of standstill. This new control system is robust with respect to variations of the stator resistance and it makes possible to calculated rotor flux at low speed of standstill. These feature are verified by the simulation results.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1046-1049
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• 2000

A direct torque control(DTC) based sensorless speed control system which employs a new closed loop flux observer is proposed. The flux observer is an adaptive gain scheduling observer where motor speed is used as the scheduling variable. Adaptive nature comes from the fact that the estimates of stator resistance and speed are included as observer parameters. Simulation results show that the proposed flux observer gives better control and estimation results than conventional flux estimator specially in low speed region.

• Journal of The Korean Astronomical Society
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• v.47 no.3
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• pp.105-113
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• 2014

We apply differential affine velocity estimator (DAVE) to the Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) 12-min line-of-sight magnetograms, and separately calculate the injected magnetic helicity for the leading and the following polarities of nine emerging bipolar active regions (ARs). Comparing magnetic helicity flux of the leading polarity with the following polarity, we find that six ARs studied in this paper have the following polarity that injected more magnetic helicity flux than that of the leading polarity. We also measure the mean area of each polarity in all the nine ARs, and find that the compact polarity tend to possess more magnetic helicity flux than the fragmented one. Our results confirm the previous studies on asymmetry of magnetic helicity that emerging bipolar ARs have a polarity preference in injecting magnetic helicity. Based on the changes of unsigned magnetic flux, we divide the emergence process into two evolutionary stages: (1) an increasing stage before the peak flux and (2) a constant or decreasing stage after the peak flux. Obvious changes on magnetic helicity flux can be seen during transition from one stage to another. Seven ARs have one or both polarity that changed the sign of magnetic helicity flux. Additionally, the prevailing polarity of the two ARs, which injects more magnetic helicity, changes form the following polarity to the leading one.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.161-165
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• 1997

For high performance ac drives, the speed sensorless vector control and the stator flux orientation concept have received increasing attention. This paper presents a new method of estimation the speed of AC induction machine(IM). To improve the speed estimation characteristics, accurate stator resistance variation is considered. The effectiveness of the proposed method is verified computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1241-1249
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• 2007

Lately, many approaches of speed sensorless control method for Interior Permanent Magnet Synchronous Motor(IPMSM) ha, been developed. This paper proposes a novel sensorless algorithm for speed estimation of IPMSM. First of all, proposes sensorless method estimates flux of rotor using foundational voltage equation of IPMSM and then estimates position and speed of rotor using Phase Locked Loop(PLL). Proposed sensorless algorithm demonstrated through simulation using Matlab simulink and experiment.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.509-511
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• 1997

A sensorless controller of induction motor has several advantage availability in a harsh environment. In this paper, the speed information is driving from the currents and the estimated stator flux. To obtain the estimated stator flux, this study is using the Estimator. The simulation results show that the proposed scheme has activity over a wide speed range and good response to load variations.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.443-447
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• 2001

In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Reference Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach. The structure of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.241-248
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• 2007

The accuracy of all the schemes that belong to vector controlled induction machine drives is strongly affected by parameter variations. The aim of this paper is to examine iron losses and magnetic saturation effect in sensorless vector control of induction machines. At first, an approach to induction machine modelling and vector control scheme, which account for both iron loss and saturation, is presented. Then, a model reference adaptive system (MRAS) based speed estimator is developed. The speed estimation is modified in such a way that iron losses and the variation in the saturation level are compensated. Thus by substituting an artificial neural network flux estimator into the MRAS speed estimator. Experimental results are presented to verify the effectiveness of the proposed approach.

• Proceedings of the KIEE Conference
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• 2000.11b
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• pp.336-338
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• 2000

Recently many studies have been performed for variable speed control of induction motor. Direct Torque Control(DTC) is emerging technique for variable speed control of PWM inverter driven induction motor. DTC allows the direct control of stator flux and instantaneous torque through simple algorithm. In this paper ASIC design technique using VHDL is applied to DTC based speed control of induction motor. ASIC for DTC based speed control is designed through the description of coordinate transformation, speed controller stator flux and torque estimator, stator flux and torque controller, stator flux position detector. FSM(Finite State Machine) and inverter voltage switching vector. Finally the above system has been implemented on the FPGA (XC4052XL-PG411). Simulation and experiment has been performed to verify the performance of the designed ASTC.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.761-762
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• 2006

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.