• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.321-328
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• 1998

When we control the level of the steam generator in the nuclear power plants, a swell and shrink arises from many disturbances such as feed water rate, feed water temperature, main steam flow rate, and coolant temperature. If we use the conventional type of PI controller in this system, we will not have stability during controlling at lower power, the removal function of disturbances, and a load follow-up control effectively. In this paper, we study the application of a 2-Degree of Freedom(2-DOF) PID controller to the level control of the steam. generator of nuclear power plants through the simulation and the experimental steam generator. We use the parameters $\alpha$, $\beta$, $\gamma$ of the 2-DOF PID controller for the removal of disturbances and the parameters Kp,Ti,Td of the conventional type of PID controller for controlling setpoint. The back-propagation learning algorithm of neural network is used for tuning the 2-DOF PID controller. We can find satisfactory results of the removal of the disturbances and the tracking function in the change of setpoint through the simulation and experimental steam generator.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2203-2205
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• 2003

In this thesis, it is a purpose to carry out speed control of DC servo motor without using encoder and the resolver which are speed sensor of DC servo motor and it should use estimate algorithm or observer and must assume a speed in order to control speed sensorless. Therefore, high gain observer was designed to estimate rotor speed of DC servo motor and it carries out speed control from the feedback of the speed that assumed done in the thesis. Also, implementation used easy PI controller in speed-controller of DC motor though it was simple. It is compared estimate performance of Luenberger and high gain observer in a way of computer simulation in order to verify performance of the high gain observer which proposed in this thesis, and proved excellency of the high gain observer. And the thesis proved that smooth speed sensorless control of DC servo motor was implemented in invariable driving.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.32-34
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good Performance over a wide range of operation, even under ideal field oriented conditions. This paper is proposed model reference adaptive fuzzy control(MFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaption mechanism(FAM), MFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, MFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.92-99
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• 2016

An electro-hydraulic actuator (EHA) is widely used in industrial motion systems and the increasing bandwidth of EHA position control is important issue. The model-inverse feedforward controller is known to extend the bandwidth of system. When the system has non-minimum phase (NMP) zeros, direct model inversion makes system unstable. To overcome this problem, an approximate model-inverse method is used. A representative approximate model inversion method is zero phase error tracking control (ZPETC). However, if zeros locate right half plane of z-plane, the approximate inverse model amplifies the high-frequency response. In this paper, to solve the problem of ZPETC, an adaptive model-inverse control is proposed. The adaptive algorithm updates feedforward term in real-time. The effectiveness of the proposed adaptive model-inverse position control strategy is verified by comparison with typical proportional-integral (PI) control and feedforward control by experiments. As a result, the proposed adaptive controller extends the bandwidth of EHA position control.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.404-407
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation even under ideal field oriented conditions. This paper is proposed adaptive fuzzy controller(AFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaptation mechanism(FAM), AFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, AFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.41-47
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• 2009

In this paper, authors performed improvement of control characteristics of an attraction type magnetic levitation system. The attraction type magnetic levitation system has an inherent instability in the system, therefore its controller must have not only proportional-integral gain but also differential gain additionally. In this paper, authors were proposed control algorithm using disturbance observer(DOB) on feedback signal. The computer simulation and experiments were performed for its verification.

• Proceedings of the KIPE Conference
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• 2008.10a
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• pp.199-201
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• 2008

In this paper proposed the solar tracking system to use direct fuzzy control order to increase an output of the PV (Photovoltaic) array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. Recently, artificial intelligent control of the fuzzy control, neural-network and genetic algorithm etc. have been studied. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up, nonlinear altitude and azimuth. In this paper designed a DFC(Direct Fuzzy Control)controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.209-209
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• 2023

본 연구에서는 강우 시 발생하는 음향 및 진동 신호를 기반으로 강우강도를 산정하기 위한 방법론을 제안하였다. 먼저, Raspberry Pi, 콘덴서 마이크 및 가속도 센서로 구성된 관측 기기로부터 실제 비가 내리는 환경에서의 음향 및 진동 신호를 수집하였다. 가속도 센서로부터 계측된 진동 신호를 활용하여 강우 유무에 대한 이진 분류를 수행하고, 강우가 발생한 것으로 판단된 기간에 해당하는 음향 신호에 Short-Time Fourier Transform 기술을 적용하여 주파수 영역에서 나타나는 magnitude의 평균과 표준 편차, 최고 주파수 등의 특징을 기반으로 강우강도를 산정하였다. 이를 위해 앙상블 기반의 머신러닝 학습 모델인 XGBoost 알고리즘을 사용하였으며, 광학 우적계를 통해 관측한 강우강도와 산정 결과를 비교·평가하였다. 강우강도 산정 과정에서 사용된 음향 신호의 길이를 1초, 10초, 1분으로 구분하였으며, 무강우 기간 내 음향 정보로부터 배경 음향에 의한 노이즈를 제거하고자 하였다. 최종적으로 강우 유무 이진 분류 과정의 선행 여부, 음향 신호의 길이 및 노이즈 제거 방법에 따른 강우강도 산정 결과들에 대한 성능 비교를 통해 본 연구에서 제안하고자 하는 방법론의 실효성을 평가하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.684-692
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• 2016

In the manufacturing process of the LQFP/TQFP (Low-profile Quad Flat Package/Thin Quad Flat Package), the requirement of a 3 dimensional inspection is increasing rapidly and a 3D inspection of the shape of a chip has become an important report of quality control. This study developed a 3 dimensional measurement system based on PMP (Phase Measuring Profilometry) for an inspection of the LQFP/TQFP chip and image processing algorithms. The defects of the LQFP/TQFP chip were classified according to the dimensions. The 2 dimensional optical system was designed by the dorm illumination to achieve constant light distribution, In the 3 dimensional optical system, PZT was used for moving 90 degree in phase. The problem of 2 ambiguity was solved from the measured moir? pattern using the ambiguity elimination algorithm that finds the point of ambiguity and refines the phase value. The proposed 3D measurement system was evaluated experimentally.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.140-149
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• 2018

Along with the recent increase in national income, social phenomena such as aging due to a decrease in population and an increase in single households are observed. There are also an increasing number of households raising pets in proportion to aging households and the increase in the number of single households, most of which use animal companions to overcome loneliness and boost domestic vitality. As more and more people consider pets as family members, the size of the domestic pet market is also growing. The growing number of pets in older households and single households is not properly managed by care such as food meals and exercise management for pets. It is necessary to research and develop robots that can monitor animal companions remotely, feed a certain amount of food at regular intervals, and manage their health through exercise. Among pet companions, dog selection is the highest. Therefore, this study identified robot research on driving methods, examples of existing pet care systems, and researched pet care robots using obstacle avoidance algorithms. In order to use the snack pay behavior and obstacle avoidance algorithm of the pet animals by applying IoT and we .oPI technology, it is able to use ultrasonic sensors on the front and has four infrared sensors on the back. However, this study does not reflect the characteristics of other pet animals as a study on pet care robots, and it requires continuous observation and testing.