• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.717-719
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• 2003

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult to the PID gains suitably lots of researches have been reported with respect to turning schemes of PID gains. A Neural Network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.89-91
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• 2004

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult to the PID gains suitably lots of researches have been reported with respect to turning schemes of PID gains. A Neural Network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal is convergence speed progress about applied gain of PID controller using the neural networks.

• Land and Housing Review
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• v.10 no.3
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• pp.9-16
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• 2019

This study aimed at developing control algorithms for operating a variable refrigerant flow (VRF) heating and cooling system with optimal system parameter set-points. Two artificial neural network (ANN) models, which were respectively designed to predict the heating energy cost and cooling energy amount for upcoming next control cycle, was developed and embedded into the control algorithms. Performance of the algorithms were tested using the computer simulation programs - EnergyPlus, BCVTB, MATLAB in an incorporative manner. The results revealed that the proposed control algorithms remarkably saved the heating energy cost by as much as 7.93% and cooling energy consumption by as much as 28.44%, compared to a conventional control strategy. These findings support that the ANN-based predictive control algorithms showed potential for cost- and energy-effectiveness of VRF heating and cooling systems.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1235-1239
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• 2003

On the base of network frame and protocol system of Ethernet the networked sensing technology based on Ethernet is studied and the design principles of industrial Ethernet measurement of control system is put forward, and the general structure model is built in the paper. An eight-bit economical MCU scheme is proposed, and a general scheme of distributed intelligent networked measuring and control equipment based on TCP/IP is designed too. A compact TCP/IP protocol stack are successfully implemented in eight-bit MCU. With C51 program language, method of modularized programming is applied in soft design. The problem of in-system modifying measuring and control strategy of its system is solved successfully by assigning memory dynamically and saving parameter with EEPROM, and it makes the intelligent networked measurement and control system can explain and analyses control strategy from PC. Experiment result shows that, the research of intelligent networked measurement and control equipment and system base on TCP/IP is successful, with flexible network, convenient usage, and good commonality.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2498-2501
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• 2003

In this paper, we present a wavelet neural network (WNN) approach to the solution of the path tracking problem for mobile robots that possess complexity, nonlinearity and noise. First, we discuss a WNN based control system where the control signals are directly obtained by minimizing the difference between the reference track and the pose of a mobile robot. This compact network structure is helpful to determine the number of hidden nodes and the initial value of weights. Then, the data with various noises provided by odometric and external sensors are here fused together by means of an Extended Kalman Filter (EKF) approach for the pose estimation problem of mobile robots. This control process is a dynamic on-line process that uses the wavelet neural network trained via the gradient-descent method with estimates from EKF. Finally, we verify the effectiveness and feasibility of the proposed control system through simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.831-833
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• 2004

In this paper, an obstacle avoidance algorithm is proposed for a network-based robot considering network delay by distribution. The proposed algorithm is based on the VFH(Vector Field Histogram) algorithm, and for the network-based robot system, in which it is assumed robot localization information is transmitted through network communication. In this paper, target vector for the VFH algorithm is estimated through the robot localization information and the measurement of its delay by distribution. The delay measurement is performed by time-stamp method. To synchronize all local clocks of the nodes distributed on the network, a global clock synchronization method is adopted. With the delay measurement, the robot localization estimation is performed by calculating the kinematics of the robot. The validation of the proposed algorithm is performed through the performance comparison of the obstacle avoidance between the proposed algorithm and the existing VFH algorithm on the network-based autonomous mobile robot.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.197-205
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• 2022

The Cyber Physical System(CPS) is an important concept in achieving SMSs(Smart Manufacturing Systems). Generally, CPS consists of physical and virtual elements. The former involves manufacturing devices in the field space, whereas the latter includes the technologies such as network, data collection and analysis, security, and monitoring and control technologies in the cyber space. Currently, all these elements are being integrated for achieving SMSs in which we can control and analyze various kinds of producing and diagnostic issues in the cyber space without the need for human intervention. In this study, we focus on implementing a production equipment monitoring system related to building a SMS. First, we describe the development of a fog-based gateway system that links physical manufacturing devices with virtual elements. This system also interacts with the cloud server in a multimedia network environment. Second, we explain the proposed network infrastructure to implement a monitoring system operating on a cloud server. Then, we discuss our monitoring applications, and explain the experience of how to apply the ML(Machine Learning) method for predictive diagnostics.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2780-2782
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• 2002

In this paper Valentine Braitenberg structure based sensory motor model for object tracking control system was proposed. Conventional model based control schemes are require highly non-linear mathematical models, which require long computational time to solve complex high order equations. Contrast to conventional models proposed system simply link signal data from camera directly to the inputs of neural network, and outputs of network are directly fed into input of motor driver of camera. With simple structure of sensory motor model, real time tracking control system for dynamic object was realized successfully, and the implementation of sensory motor model can overcome the limitation of model-based control schemes.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.600-603
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• 2000

In this paper, we propose the design method of distributed control system using Controller Area Network (CAN). CAN is an advanced serial communication protocol for distributed real-time control systems. It is a contention-based multi-master network whose timeliness properties come from its collision resolution algorithm which gives a high schedulable utilization and guaranteed bus access latency. With proposed method using CAN, we apply to robot controller. The effectiveness of proposed method is demonstrated by the simulation and experiment.

• Convergence Security Journal
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• v.7 no.4
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• pp.1-8
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• 2007

Currently, the needs of open standard and integrated network, and also applications of Ethernet network based system are increasing. By applying and expanding TCP/IP based network technology from high to low control level, factory automation application has been implemented, and thus integrated factory automation system has been accomplished, which is directly interoperable between high level management program and DB system. This paper proposes a communication control device which is based on Ethernet/IP standard system for factory automation. The proposed system is workable in the environment of a network system, which is based on CIP standard interface technology. The proposed system can also contribute to improve data communication characteristics.