• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.7
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• pp.15-25
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• 2011

This proposes an online loss minimization algorithm for series PI(SPI) based interior permanent magnet synchronous motor(IPMSM) drive to yield high efficiency and high dynamic performance over wide speed range. The loss minimization algorithm is developed based on the motor model. In order to minimize the controllable electrical losses of the motor and thereby maximize the operating efficiency, the d-axis armature current is controlled optimally according to the operating speed and load conditions. For vector control purpose, a SPI is used as a speed controller which enables the utilization of the reluctance torque to achieve high dynamic performance as well as to operate the motor over a wide speed range. Also, this paper proposes current control of model reference adaptive fuzzy controller(MFC), and estimation of speed using artificial neural network(ANN) controller. The proposed efficiency optimization control, SPI, MFC, ANN in this paper is applied to IPMSM drive system, the validity of this paper is proved by analyzing response characteristics in variety operating conditions.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.145-155
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• 2010

This paper presents a new approach to obstacle avoidance for mobile robot in unknown or partially unknown environments. The method combines two navigation subsystems: low level and high level. The low level subsystem takes part in the control of linear, angular velocities using a multivariable PI controller, and the nonlinear position control. The high level subsystem uses ultrasonic and IR sensors to detect the unknown obstacle include static and dynamic obstacle. This approach provides both obstacle avoidance and target-following behaviors and uses only the local information for decision making for the next action. Also, we propose a new algorithm for the identification and solution of the local minima situation during the robot's traversal using the set of fuzzy rules. The system has been successfully demonstrated by simulations and experiments.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.95-97
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• 1997

This paper deals with design and implementation of the controller for optically guided AGV. When AGV has only three photo sensors in front of body, AGV doesn't know how much the entry angle to guide line is. In this case, it is difficult to compensate the tracking error. To make sure that the AGV does not secede the guide line in tracking, PI controller and fuzzy logic controller is proposed. The proposed controller was verified and experienced through real AGV system.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.149-151
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• 2001

This paper proposes the design of STATCOM(static synchronous compensator) stabilizer for improving power system stability using fuzzy logic controller(FLC). The STATCOM DC voltage regulator contributes negative damping to the power system as the installation of STATCOM DC voltage regulator. STATCOM stabiliser is superimposed on the AC voltage regulator to compensate the negative damping effect. To evaluate usefulness of the proposed method, we perform the nonlinear simulation on a single-machine infinite bus system. As results of the simulations, the proposed method shows better control performance than PI controller in terms of damping effects.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1034-1036
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• 1996

In this paper, an adaptive fuzzy logic controller is presented for auto-tunning of the scaling factors by using learning capability of neural networks. The proposed scheme consists of the FLC which includes the PI-type FLC and PD-type FLC in parallel form and the neural network which learns scale factors of FLC. Computer simulations were performed to illustrate the effectiveness of a proposed scheme. A proposed FLC controller was applied to the second order system and velocity control of the brushless DC motors. For the design of the FLC, tracking error, change of error, and acceleration error are selected as input variables of the FLC and three seal e factors were used in the parallel-type FLC. This scheme can be used to reduce the difficulty in the selection of the scale factors.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2316-2318
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• 2003

본 논문에서는 지게차용 12KW급 대전류 SR모터의 전류의 진상각 및 오프각 제어와 속도의 퍼지 제어에 대해 기술하였다. 대전류 SR모터의 경우는 전압이 낮은 대신 큰 전류가 흘러야 한다. 때문에 저 저항, 저 인덕턴스 형태로 설계된다. 따라서 토크가 유발되는 인덕턴스 상승구간에 원하는 크기의 전류를 얻기 위해서는 인덕턴스의 상승구간 이전에 적절히 스위칭 시켜 주어야 하는데 이를 진상각 제어라 하고, 역토크 구간 인 인덕턴스의 감소구간 이전에 스위칭 시켜주는 것을 오프각 제어라 한다. 이러한 내용을 실구동 실험을 통하여 얻은 토크 및 속도의 변화에 따른 진상각 및 오프각의 가변 데이터를 Look-up 테이블로 만들어 시뮬레이션을 통해 실험을 해본다. 또한 실험을 통한 데이터를 바탕으로 퍼지 제어기를 구성하여 시뮬레이션을 통해 PI 제어기와 비교 분석하여 본다.

• Journal of Energy Engineering
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• v.6 no.2
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• pp.170-175
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• 1997

An experimental study was carried out with the Mock-up made for the improved water level control of the steam generator in nuclear power plant and for the confirmation of swell/shrink status of the water level by opening and closing the steam dump valve. We can confirmed the possibility of using the Mock-up by introducing the PI controller and the FUZZY controller. Accordingly, we can confirmed that the practical usability of advanced controllers, which will be developed for the improved water level control of the steam generator in nuclear power plant by using the Mock-up.

• Nuclear Engineering and Technology
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• v.25 no.2
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• pp.222-232
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• 1993

In this paper, we present two sets of fuzzy algorithms for the steam generator level control ; one for the high power operations where the flow error is available and the other for the low power operations where the flow error is not available. These are converted to a PID type controller for the high power case and to a quadratic function form of a controller for the low power case. These controllers are implemented on the Compact Nuclear Simulator at Korea Atomic Energy Research Institute and tested by a set of four simulation experiments for each. For both cases, the results show that the total variation of the level error and of the flow error are about 50% of those by the PI controllers with about one half of the control action. For the high power case, this is mainly due to the fact that a combination of two PD type controllers in the velocity algorithm form rather than a combination of two PI type controllers in the position algorithm form is used. For the low power case, the controller is essentially a PID type with a very small integral component where the average values for the derivative component input and for the controller output are used.