• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.361-361
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• 2000

In the 2-mass system with flexible shaft, a torsional vibration is often generated because of the elastic elements in torque transmission as the newly required speed response which is very close to the primary resonant frequency. This vibration makes it difficult to achieve quick responses of speed and disturbance rejection. In this paper, 2-mass system is designed by using pole placement based on optimal control theory fur fast speed response and torsional vibration elimination and using neural network for disturbance rejection in particular. The simulation results show that the proposed controller based on neural network and full state feedback controller has better performance than 려ll state feedback controller, especially fur disturbance rejection.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.248-250
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• 1993

In this paper, we assume that the dynamics of DC motor and nonlinear load are unknown. We train the inverse dynamic model of DC motor and nonlinear load using the neural network and construct speed control system based on the traind dynamic model and current control mode. Speed prediction scheme using neural network is also proposed the alleviate the time delay effect caused by the computation time of neural network. Simulation results show good performances of the control system. Finally, hardware configuration of the control system is outlined.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.235-238
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• 1996

In this paper, a new optimization method which is a kind of random searching is presented. The proposed method is called RasVal which is an abbreviation of Random Search Method with Variable Seaxch Length and it can search for a global minimum based on the probability density functions of searching, which can be modified using informations on success or failure of the past searching in order to execute intensified and diversified searching. By applying the proposed method to a nonlinear crane control system which can be controlled by the Universal Learning Network with radial basis function(R.B.P.), it has been proved that RasVal is superior in performance to the commonly used back propagation learning algorithm.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.9
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• pp.485-490
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• 2006

According to the computerization of railway signaling systems, the interface link between the signaling systems has been replaced by the digital communication channel. At the same time, the importance of the communication link is more pronounced than before. In this paper, new Network-based protocol between railway signaling and SCADA (Supervisory Control and Data Acquisition system) has designed and the overview of designed protocol is briefly represented. And also this paper addresses analysis of newly designed train control systems. Fame error rates of the data transmissions are calculated and compared for the two cases that the CTC (Centralized Traffic Control)/SCADA has an extra data transmission error control (CRC16) besides the inherent error control of the Ethernet and that the CTC/SCADA has no extra data transmission error control. With simulation results it has been verified that the additional error control code contributes to lowering the frame error rate. It will be expected to increase the safety, reliability and efficiency of maintenance of the signaling systems by using the designed protocol for railway signaling system.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.102-108
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• 2018

The existing data transmission technology applied between the non-secure external internet and the secure internal business network has various problems when applied to the building facility management SCADA system control network. Traditional inter-network data transfer technologies involve high complexity and high costs because blacklist-based security techniques are applied to all data. However, whitelist-based security techniques can be applied to data distributed in Building Facility Management SCADA control systems because a small number of structured control data are repeatable and periodic. This simplifies the security technology applied to inter-network data transmission, enabling building facility management SCADA system control network deployment at low cost. In this paper, we proposed building control networks specialized in building facility management SCADA control systems by providing solutions to address and address these problems.

• Journal of the Society of Naval Architects of Korea
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• v.34 no.2
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• pp.56-63
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• 1997

This paper is concerned with the design of neural-network based autopilot control system. In this paper, the back-propagation algorithm is introduced and explained in detail. The system identification method based on neural networks for ship motion is developed and its efficacy is verified by using a simple ship maneuvering model. Problems which may arise in a complex maneuvering model are then discussed. The neural-network based system identification method developed in this paper can be used effectively for reconstructing the ship maneuvering moodel which is known to have nonlinearity.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.118.2-118
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• 2002

Uncertain time delay happens when the process reads the sensor data and sends the control input to the plant located at a remote site in distributed control system. As in the case of data network using TCP/IP, VDN that integrates both device network and data network has uncertain tim e delay. Uncertain time delay can cause degradation in stability of distributed control system based on VDN. This paper investigates the transmission characteristic of VDN and suggests a control scheme based on the Smith's predictor to minimize the effect of uncertain time delay. The validity of the proposed control scheme is demonstrated with tracking position control of experiments.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.1-8
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• 2021

With the rapid growth of intelligent devices and communication technologies, 5G network environment has become more heterogeneous and complex in terms of service management and orchestration. 5G architecture requires supportive technologies to handle the existing challenges for improving the Quality of Service (QoS) and the Quality of Experience (QoE) performances. Among many challenges, traffic steering is one of the key elements which requires critically developing an optimal solution for smart guidance, control, and reliable system. Mobile edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), and deep learning (DL) play essential roles to complementary develop a flexible computation and extensible flow rules management in this potential aspect. In this proposed system, an accurate flow recommendation, a centralized control, and a reliable distributed connectivity based on the inspection of packet condition are provided. With the system deployment, the packet is classified separately and recommended to request from the optimal destination with matched preferences and conditions. To evaluate the proposed scheme outperformance, a network simulator software was used to conduct and capture the end-to-end QoS performance metrics. SDN flow rules installation was experimented to illustrate the post control function corresponding to DL-based output. The intelligent steering for network communication traffic is cooperatively configured in SDN controller and NFV-orchestrator to lead a variety of beneficial factors for improving massive real-time Internet of Things (IoT) performance.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1137-1147
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• 2004

In this paper, we proposed two types of adaptive control mechanism which is named HIA(Humoral Immune Algorithm) PID and CMIA(Cell-Mediated Immune Algorithm) controller based on biological immune system under engineering point of view. The HIA PID which has real time control scheme is focused on the humoral immunity and the latter which has the self-tuning mechanism is focused on the T-cell regulated immune response. To verify the performance of the proposed controller, some experiments for the control of AGV which is used for the port automation to carry container without human are performed. The experimental results for the control of steering and speed of an AGV system illustrate the effectiveness of the proposed control scheme. Moreover, in that results, proposed controllers have better performance than other conventional PID controller and intelligent control method which is the NN(neural network) PID controller.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.1-10
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• 2020

This paper is a IoT-based radon meter control system and a radon meter control method using it. The IoT-based radon meter control system is control system for controlling a radon meter by network-connecting radon meter and a user terminal. The radon measuring device may be provided with a radon sensor to measure a radon value of a preset management target area, it collect and store numerical data. The radon meter control system monitors the condition of the radon meter, it includes control center configured to deliver radon meter management information generated to a user terminal. Also radon measurements to determine the exact amount of radon gas. Therefore, the situation-specific actions based on radon numbers can be promptly implemented to ensure adequate protection for those who are vulnerable to radon and those who live in the area. Condition monitoring allows the radon meter to respond quickly to failure or failure of the radon meter. In addition, it is possible to secure a baseline of radon's influence and to obtain research data to cope with radon by establishing big data with radon measurements.