• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제51권2호
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• pp.69-76
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• 2002

To obtain a high performance in a vector controlled induction motor, it is essential to know the instantaneous position of the rotor flux which depends on the rotor time constant. But the rotor time constant mainly varies due to the temperature rise in the motor winding, so real time compensating algorithm is necessary. This paper proposes that it uses short duration pulses added to the constant flux command current and then resultant torque command current produced by speed controller is utilized for the rotor resistance estimation. This method has advantage with a low computational requirement and does not require voltage sensors. The proposed method is proved by simulations and experimentals.

• Journal of Power Electronics
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• 제12권6호
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• pp.1003-1010
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• 2012

Recent power electronics and variable-frequency motor drive technologies have been applied to air conditioners to improve efficiency and power density. However, the mechanical vibrations and acoustic noise resulting from the compressor still remain as a serious problem. This paper presents the development and implementation of an online disturbance state-filter for the suppression of multiple unknown and time-varying vibrations of air conditioning systems. The proposed design has a form of the state-filter based on a Luenburger-style closed-loop speed observer. An active vibration decoupling strategy with an estimated disturbance is provided, which manipulates a motor torque command. Since the proposed estimation does not require any additional transducers or hardware for obtaining real-time information upon disturbances, it is suitable for retrofitting industrial air conditioners.

• Journal of Power Electronics
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• 제12권5호
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• pp.758-768
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• 2012

This paper presents the modeling and position-sensorless vector control of a dual-airgap axial flux permanent magnet (AFPM) machine optimized for use in flywheel energy storage system (FESS) applications. The proposed AFPM machine has two sets of three-phase stator windings but requires only a single power converter to control both the electromagnetic torque and the axial levitation force. The proper controllability of the latter is crucial as it can be utilized to minimize the vertical bearing stress to improve the efficiency of the FESS. The method for controlling both the speed and axial displacement of the machine is discussed. An inherent speed sensorless observer is also proposed for speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a prototype machine.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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• pp.302-304
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• 1996

In this paper, a new algorithm for sensorless speed control of switched reluctance motor (SRM) is proposed. It is based on the measurement of initial rate of change of phase current. The initial rate of rise of phase current mainly depends up on the phase inductance at the time instant when the phase is excited. Therefore, the measurement of initial di/dt permits rotor position estimation, which is used to trigger the next phase. In the proposed technique, there is no need to generate additional current pulses when a phase is not excited. Therefore, this scheme does not introduce the unwanted braking torque. Also, only one current measurement is made every time a phase is excited. This reduces the computational load on the micro-controller and enhances the speed range of the sensorless drive. By using this scheme it is possible to implement the sensorless control of SRM using low cost micro-controller.

• 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.

• 로봇학회논문지
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• 제1권1호
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• pp.81-88
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• 2006

Control of a robot manipulator in contact with the environment is usually conducted by the direct feedback control using a force-torque sensor or the indirect impedance control. In these methods, however, the control algorithms become complicated and the performance of position and force control cannot be improved because of the mechanical properties of the passive components. To cope with such problems, redundant actuation has been used to enhance the performance of position control and force control. In this research, a Double Actuator Unit (DAU) is proposed, with which the force control algorithm can be simplified and can make the robot ensure the safety during the external collision. The DAU is composed of two actuators; one controls the position and the other modulates the joint stiffness. Using this unit, it is possible to independently control the position and stiffness. The DAU based on the planetary gears is investigated in this paper. Performance using the DAU is also verified by various experiments. It is shown that the manipulator using this mechanism provides better safety during the impact with the environment by reducing the joint stiffness appropriately on detecting the collision of a manipulator.

• 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.

• 한국산학기술학회논문지
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• 제16권5호
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• pp.3030-3034
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• 2015

새로운 엔진과 차량을 개발하여 엔진을 차량에 탑재할 때, 중요하게 고려해야 할 사항 중의 하나는 냉각 성능이다. 만약 냉각 성능이 열악하다면 엔진은 과열되어 파손되게 된다. 그러나 자동차회사에서 일반적으로 엔진은 차량보다 훨씬 빠른 시기에 개발이 진행되게 되어 엔진을 차량에 탑재한 조건에서 냉각 성능을 시험할 수 없다. 본 연구에서는 몇 가지 시험과 계산 결과를 이용하여 엔진의 냉각 성능을 추정하였다. 첫 번째로 엔진의 열정산 시험이 진행되었다. 두 번째로 냉각수 유동 시험이 진행되었다. 이 시험에서 라디에이터로 유입되는 유량을 구할 수 있다. 그리고 차량의 냉각 시험 성능 조건으로부터 차량의 부하와 속도를 구하고, 이로부터 엔진의 토크와 rpm이 계산되었다. 그리고 이러한 결과를 비교하여 엔진의 냉각 성능이 추정되었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 B
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• pp.1453-1455
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• 2005

This paper presents self tuning PI controller of IPMSM drive using neural network. Self tuning PI 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 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 fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 대한임베디드공학회논문지
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• 제16권4호
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• pp.137-143
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• 2021

We propose an adaptive non-singular terminal sliding-mode control for the fast finite-time convergence (FANTSMC) in robot manipulator. The proposed FANTSMC approach is developed to be applied without singularity in robot manipulator, which has a new pole-placement control with the non-singular terminal sliding variable while generating the desirable control torque. Moreover, the switching gain is designed to suppress the time-delayed estimation error appropriately, which aims at providing the high robust tracking performance. Also, the proposed one employs one-sample delayed information to cancel out the system uncertainties and disturbances. For these reasons, it offers strong attraction within the finite time. It is shown that the tracking performance of the proposed FANTSMC approach is guaranteed to be uniformly ultimately bounded through the Lyapunov stability. The effectiveness of the proposed FANTSMC approach is illustrated in simulations, which is compared with that of the up-to-date control approach.