• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.4
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• pp.16-21
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• 2013

This paper presents a DC link voltage control method to reduce the ripple current and the switching loss in the sinusoidal current drive system for the wide-speed range PMSM. The DC link voltage of the three phase inverter in the sinusoidal current drive system is designed by the back-EMF voltage at maximum speed of the PMSM. In general, the drive systems have used the constant DC link voltage without reference to the motor speed. The current ripple causes hysteresis loss and makes noise. In addition, the switching loss on the inverter increases in proportion to the rise in the DC link voltage. In this paper, we propose the variable DC link voltage control method to reduce the current ripple in the PMSM drive system. We show reduction effect of the current repple and the switching loss through simulation results.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.529-538
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• 2015

Due to the high efficiency and compact mechanical structure, direct drive variable speed generators are used for power conversion in wind turbines. The wind energy conversion system (WECS) considered in this paper consists of a permanent magnet synchronous generator (PMSG), uncontrolled rectifier, dc-dc boost converter controlled with maximum power point tracking (MPPT) and adaptive hysteresis controlled voltage source inverter (VSI). For high utilization of the converter's power capability and stabilizing voltage and power flow, constant DC-link voltage is essential. Step and search MPPT algorithm which senses the rectified voltage ($V_{DC}$) alone and controls the same is used to effectively maximize the output power. The adaptive hysteresis band current control is characterized by fast dynamic response and constant switching frequency. With MPPT and adaptive hysteresis band current control in VSI, the DC link voltage is maintained constant under variable wind speeds and transient grid currents respectively.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.361-365
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• 1998

In this paper, the sliding mode variable structure-fuzzy(SMVS-F) control algorithm is applied to speed controller for field oriented induction motor drive system. According to the principle of sliding mode variable structure-fuzzy adjustable speed control scheme, the proposed algorithm shows good performances which are reducing chattering, robustness against parameter variation in induction motor drive. The validity of the proposed control scheme is verified by computer simulation using SIMULINK.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.215-225
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• 2011

In this paper, a buck DC-DC bridge converter is used as a power factor correction (PFC) converter for feeding a voltage source inverter (VSI) based permanent magnet brushless DC motor (PMBLDCM) drive. The front end of the PFC converter is a diode bridge rectifier (DBR) fed from single phase AC mains. The PMBLDCM is used to drive the compressor of an air conditioner through a three-phase voltage source inverter (VSI) fed from a variable voltage DC link. The speed of the air conditioner is controlled to conserve energy using a new concept of voltage control at a DC link proportional to the desired speed of the PMBLDC motor. Therefore, VSI operates only as an electronic commutator of the PMBLDCM. The current of the PMBLDCM is controlled by setting the reference voltage at the DC link as a ramp. The proposed PMBLDCM drive with voltage control-based PFC converter was designed and modeled. The performance is simulated in Matlab-Simulink environment for an air conditioner compressor load driven through a 3.75 kW, 1500 rpm PMBLDC motor. To validate the effectiveness of the proposed speed control scheme, the evaluation results demonstrate improved efficiency of the complete drive with the PFC feature in a wide range of speed and input AC voltage.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.249-256
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive learning mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control (FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, FLC and ANN controller.

• Journal of Drive and Control
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• v.9 no.4
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• pp.71-78
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• 2012

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.224-234
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• 2008

Multi-phase machines can be used in variable speed drives. Their applications include electric ship propulsion, 'more-electric aircraft' and traction applications, electric vehicles, and hybrid electric vehicles. Multi-phase machines enable independent control of a few numbers of machines that are connected in series in a particular manner with their supply being fed from a single voltage source inverter(VSI). The idea was first implemented for a five-phase series-connected two-motor drive system, but is now applicable to any number of phases more than or equal to five-phase. The number of series-connected machines is a function of the phase number of VSI. Theoretical and simulation studies have already been reported for number of multi-phase multi-motor drive configurations of series-connection type. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the sensor, information concerning the rotor speed is extracted from measured stator currents and voltages at motor terminals. Open-loop estimators or closed-loop observers are used for this purpose. They differ with respect to accuracy, robustness, and sensitivity against model parameter variations. This paper analyses operation of an MRAS estimator based sensorless control of a vector controlled series-connected two-motor five-phase drive system with current control in the stationary reference frame. Results, obtained with fixed-voltage, fixed-frequency supply, and hysteresis current control are presented for various operating conditions on the basis of simulation results. The purpose of this paper is to report the first ever simulation results on a sensorless control of a five-phase two-motor series-connected drive system. The operating principle is given followed by a description of the sensorless technique.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.1
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• pp.57-64
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• 2006

This paper is proposed for a artificial neural network(ANN) sensorless control based on the vector controlled induction motor drive, or proposes a adaptive fuzzy teaming control(AFLC). The fuzzy logic principle is first utilized for the control rotor speed. AFLC scheme is then proposed in which the adaptation mechanism is executed using fuzzy logic. Also, this paper is proposed for a method of the estimation of speed of induction motor using ANN Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the analysis results to verify the effectiveness of the new method.

• Proceedings of the KIEE Conference
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• summer
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• pp.1251-1253
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neuro-fuzzy control(NFC) and estimation of speed using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.379-384
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• 2004

A prototype of 750 kW direct-drive wind turbine generator system, KBP-750D is under development in Korea. For the gearless, direct-drive prototype a synchronous generator with permanent magnets has been developed. The upwind 3-blade type machine employs variable speed and pitch control. The operating ranges of wind and rotor speed are 3 to 25 m/s and 9 to 25 rpm, respectively. The tip speed ratio of rotor blade is 7.5, designed for power coefficient 0.47, The blade pitch and torque are controlled with the predefined torque-speed curve according to the conditions of wind and public electric grid. This paper describes the outlines of primary components of KBP-750D.