• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.687-690
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• 2003

This paper presents the development of Programmable Logic Controller (PLC) and network to design the redundant control system in order to control the high priority process. The industrial process that cannot be shutdown or the effect of the shutting down takes abundantly damage. In this article, we say that the high priority process. The redundant systems are designed for controlling the high priority process that the control system must have many controllers to instead the main controller when it has some error. This paper we designed the redundancy control system by the advantage of the high-speed communication on the PLC’s network. The temperature control system and the traffic light control system used as the case study. Each example processes consist of two sets of controller. Our scheme we can increase the reliability prevents process down time and reduces the cost of opportunity to loss also.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2231-2233
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• 2002

Recently NCS(Networked Control System) is widely used in distributed control system design. The insertion of the network in the feedback control loop makes the analysis and design of NCS complex. Especially, the network-induced delay can vary the system stability and even destabilizes the entire control system. This paper deals with the stability analysis method of NCS. Also, we analyze the influence of sampling period and network-induced delay on power plant stability.

• Journal of Mechanical Science and Technology
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• 제20권5호
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• pp.591-601
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• 2006

In this paper, we present a new control methodology for perturbed crane systems. Nonlinear crane systems are transformed to linear models by feedback linearization. An inverse dynamic equation is applied to compute the system PD control force. The PD control parameters are selected based on a nominal model and are therefore suboptimal for a perturbed system. To achieve the desired performance despite model perturbations, we construct a neural network auxiliary controller to compensate for modeling errors and disturbances. The overall control input is the sum of the nominal PD control and the neural auxiliary control. The neural network is iteratively trained with a perturbed system until acceptable performance is attained. We apply the proposed control scheme to 2- and 3-degree-of-freedom (D.O.F.) crane systems, with known bounds on the payload mass. The effectiveness of the control approach is numerically demonstrated through computer simulation experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2341-2344
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• 2001

In recent years the neural network known as a sort of the intelligent control strategy is used as a powerful tool for designing control system since it has learning ability. But it is difficult for neural network controllers to guarantee the stability of control systems. In this paper we try connecting a radial basis function network to an adaptive control strategy. Radial basis function networks are simpler and easier to handle than multilayer perceptrons. We use the radial basis function network to generate control input signals that are similar to the control inputs of adaptive control using linear reparameterization of the robot manipulator. We adopt the saturation function as an auxiliary controller. This paper also proves mathematically the stability of the control system under the existence of disturbances and modeling errors.

• 제어로봇시스템학회논문지
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• 제12권6호
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• pp.614-620
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• 2006

Today the automobile has been changed from a mechanical system to an electronic control system fly the development of the electronic technology. In the automobile body, most of these electronic control devices are networked and managed fully by the CAN protocol. But, when a network system is overloaded, unexpected transmission delay for relative low priority objects occurs due to the static priority definition of the CAN protocol. To resolve this problem, this paper proposes a dynamic precedence queue mechanism that creates a queue for the low priority object and its relevant objects to be transmitted, which becomes urgent in an overloaded network system to keep the maximum allowable time delay. For the generated queue, the highest priority is assigned to transmit the queued objects within the shortest time. The mechanism is implemented in the logical link layer of CAN, which does not require any modification of the old CAN hardware. Effectiveness of the proposed mechanism is verified by the real experiments with an automobile network system.

• 한국인터넷방송통신학회논문지
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• 제15권3호
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• pp.125-130
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• 2015

본 논문에서는 네트워크에뮬레이터를 활용한 지휘통제시스템의 시험환경 구성, 결과 및 설계반영사항에 대해 다룬다. 정보통신기술의 발달에 의한 정보교환능력과 연산능력의 강화는 네트워크중심전이라는 개념을 가져오게 되었는데, 네트워크중심전에서 무기체계사용자가 빠른 상황판단을 내려 적합한 명령을 내릴 수 있게 지원하는 것이 지휘통제 체계이다. 본문에서는 소프트웨어 기반 네트워크 에뮬레이터중 하나인 dummynet을 활용한 시험환경 구축을 설명하고, 개발된 지휘통제시스템의 운용개념을 요약하였다. 더 나아가 시험 케이스 및 결과에 대해 설명하고, 목표 통신망에서의 제약사항을 극복할 운용개념을 제시하였다. 제안한 방식을 활용하면 항적메시지와 같이 여러 단말기가 같은 데이터를 빠른 주기로 공유할 때 유통 데이터를 크게 감소시킬 것으로 기대된다.

• 센서학회지
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• 제28권1호
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• pp.64-70
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• 2019

Wireless sensors have been developed in numerous ways for enhancing the convenience of installation, management and maintenance of sensors. Energy harvesting wireless sensors, which can collect energy from the external environment for permanent usage without the need of recharging and exchanging batteries, have been developed and employed used in Internet of Things and at various industrial sites. Energy harvesting wireless sensors are significantly affected by the sensor lifespan to sudden variation in the external environment. Furthermore, reduction in the sensor operating timespan can greatly affect the characteristics of the devices connected through a network. In this paper, a system performance index is proposed that can comprehensively evaluate the lifespan of a solar cell wireless sensor, determine the characteristics of devices connected to the associated network, and recommend dynamic power distribution control for improving the system performance index. Improvement in the system performance index was verified by applying the proposed dynamic power distribution control to an air conditioner network system using a solar cell wireless sensor. Obtained results corroborate that the dynamic power distribution control can extend the lifespan of the incorporated wireless sensor and reduce the air conditioner's power consumption.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.131-134
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• 1995

We developed a visual system that is able to track the moving objects within a certain range of errors. The visual system is driven by two DC servo motors that are controlled by a computer based on the visual data obtained from a CCD video camera. The software to track the moving objects is developed based on the PWM of the DC motors. Also, the problems how to implement a fuzzy logic control method and a neural network in this system, are also considered in order to check the control performance of tracking. The fuzzy logic algorithm is a powerful control technique for nonlinear dynamical system and also the neural network could be implemented in this system. In this paper, we present configuration of tracking system developed in our laboratory, the control methods of the visual system and the experimental results are shown.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.1129-1134
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• 1989

In this paper, we propose a neural network for learning to control semi-linear dynamical systems. The network is a composite system of four three-layer backpropagation subnetworks, and is able to control inverted pendulums better than systems based on modern control theory at least in some ranges of parameters. Three of the four subnetworks in our network system process angles, velocities, and positions of a moving inverted pendulum, respectively. The outputs from those three subnetworks are input to the remaining subnetwork that makes control decisions. Each of the four subnetworks learns connection weights independently by backpropagation algorithms. Teaching signals are given by the human operator. Also, input signals are generated by the human operator, but they are converted by preprocessors to actual input data for the three subnetworks except for the network for control decisions. The whole system is implemented on both of 16 bit personal computers and 32 bit workstations. First, we briefly provide the research background and the inverted pendulum problem itself, followed by the description of our composite neural network model. Next, some results from the simulation are given, which are subsequently compared with the results from a control system based on modern control theory. Then, some discussions and conclusion follow.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.96-98
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• 1993

In accordance with increase of electrical power demanded, more efficient supervisory control of distribution system is required. This study contains development of MMI(man-machine-interface) system with GUI(graphic-user-interface), for the automatic power distribution system. The main function of MMI system are to edit network of power distribution, to view network, to warnning a breakdown and to management of data base for network. The GUI function of MMI system enables more efficient management of power distribution system.