• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2017년도 제48회 춘계학술대회논문집
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• pp.139-141
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• 2017

하이브리드 로켓 추진장치에서 유량제어밸브는 HR 모터조립체로 유입되는 $N_2O$ 산화제의 유량을 변경하여 추력을 증가시키거나 감소시키는 역할을 수행한다. 본 논문에서는 응답속도를 약 1초 이내, 토크 $36N{\cdot}m$의 요구사항에 맞춰 유량제어밸브를 설계 및 제작하였다. 그리고 나서 0~10V의 아날로그 신호를 인가하였을 때 밸브가 열고 닫히는 상황을 구현하기 위해 액추에이터에 데이터 값을 입력하였다. 마지막으로 연소시험을 통해 유량제어밸브의 성능을 확인하였다.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제49권8호
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• pp.557-564
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• 2000

A very simple control approach using neural network for the robust position control of a Permanent Magnet Synchronous Motor(PMSM) is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust PMSM system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a feedforward recall and error back-propagation training. Since the total number of nodes are only eight, this system can be easily realized by the general microprocessor. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. In addition, the robustness is also obtained without affecting overall system response. This method is realized by a floating-point Digital Signal Processor DS1102 Board (TMS320C31).

• Journal of Power Electronics
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• 제5권3호
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• pp.198-205
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• 2005

The mechanical system of a drive can often be modeled as a two- or three-mass-system. The load is coupled to the driving motor by a shaft able to perform torsion oscillations. For the automatic tuning of the control, it is necessary to know the mathematical description of the system and the corresponding parameters. As the manpower and setup-time necessary during the commissioning of electrical drives are major cost factors, the development of self-operating identification strategies is a task worth pursuing. This paper presents an identification method which can be utilized for the assisted commissioning of electrical drives. The shaft assembly can be approximated as a two-mass non-rigid mechanical system with four parameters that have to be identified. The mathematical background for an identification procedure is developed and some important implementation issues are addressed. In order to avoid the excitation of the system with its natural resonance frequency, the frequency response can be obtained by exciting the system with a Pseudo Random Binary Signal (PRBS) and using the cross correlation function (CCF) and the auto correlation function (ACF). The reference torque is used as stimulation and the response is the mechanical speed. To determine the parameters, especially in advanced control schemes, a numerical algorithm with excellent convergence characteristics has also been used that can be implemented together with the proposed measurement procedure in order to assist the drive commissioning or to achieve an automatic setting of the control parameters. Simulations and experiments validate the efficiency and reliability of the identification procedure.

• Journal of Power Electronics
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• 제7권3호
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• pp.222-232
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• 2007

This paper presents the application of a single phase AC-to-DC converter using a three-phase series parallel (SPRC) resonant converter to variable speed dc-drive. The improved power quality converter gives the input power factor unity over a wide speed range, reduces the total harmonic distortion (THD) of ac input supply current, and makes very low ripples in the armature current and voltage waveform. This soft-switching converter not only possesses the advantages of achieving high switching frequencies with practically zero switching losses but also provides full ranges of voltage conversion and load variation. The proposed drive system is the most appropriate solution to preserve the present separately excited de motors in industry compared with the use of variable frequency ac drive technology. The simulation and experimental results are presented for variable load torque conditions. The variable frequency control scheme is implemented using a DSP- TMS320LF2402. This control reduces the switching losses and current ripples, eliminates the EMI and improves the efficiency of the drive system. Experimental results confirm the consistency of the proposed approach.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.225-227
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed artificial intelligent-PI(AIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 전력전자학술대회 논문집
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• pp.475-478
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• 2001

In performing the three-level SVPWM, it is nearly impossible to control the neutral-point potential exactly to the half of the dc-link voltage at all times. Therefore the inverter would produce an erroneous output voltage by this voltage unbalance. So the voltage unbalance has to be compensated in doing PWM, when the voltage unbalance occurs whether it is small or large, to make the inverter output voltage follow the reference voltage exactly the same. In this paper, a new compensating method for the neutral-point potential variation in a three-level inverter space vector PWM (SVPWM) is presented. By using the proposed method, the output voltage of the inverter can be made same as the reference voltage and thus the current and torque ripple of the inverter driven motor can be greatly improved even if the voltage unbalance is quite large. The proposed method is verified experimentally with a 3-level IGBT inverter.

• 한국정보전자통신기술학회논문지
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• 제5권3호
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• pp.117-126
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• 2012

논문에서는 극저속 영역 및 저속 영역에서 안정적이고 동특성이 우수한 벡터제어 시스템을 구성하여, 축소차원 상태관측기를 이용한 순시속도 관측기와 극저속 제어에 관한 방법을 제안하였다. 본 시스템에서 제안된 관측기는 축소차원 상태관측기를 부하토크 추정에 적용하여 속도추정에 이용함으로서 시스템구성을 간단히 구현하면서도 극저속 영역에서 정확한 순시속도 추정이 가능하였다. 또한, 시스템 잡음에 의한 영향을 줄이고, 관측기의 극을 변화시키는 일 없이 부하외란이나 모델화 오차, 측정 잡음 등에 강인한 유도전동기 속도제어 시스템을 제시하였다.

• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1285-1293
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• 2018

This paper proposes a new type of consequent-pole permanent-magnet (CPPM) machine with stator axial magnetic ring that increases torque capability over a wide speed range and enhances efficiency for the built-in rare-earth permanent magnet synchronous machine used in new energy vehicles. The excitation winding of the CPPM hybrid excitation synchronous machine in the stator is replaced by ferrite magnetic ring to simplify the structure and manufacturing process of the machine. The basic structure and magnetic regulation principle of the proposed machine are introduced and compared with the traditional interior rare-earth permanent magnet synchronous machine and CPPM hybrid excitation synchronous machine. Finally, experimental results of a new type of CPPM synchronous motor prototype with axial magnetic ring are introduced in the paper.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2006년도 춘계학술대회 논문집
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• pp.315-320
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• 2006

This paper presents speed control of IPMSM drive using neural network(NN) PI controller. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, NNPI controller proposes a new method based neural network. NNPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network 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 results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fired gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 춘계학술대회 논문집
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• pp.420-423
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.