• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.491-493
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• 2007

This paper is suggesting the method to embody Multi-Axes robot controller by using CAN which has been the most popular industrial networks. The robot controller guarantees the efficiency and reliability by using CAN as a communication tool between upper robot control parts and lower control parts.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.4
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• pp.312-320
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• 2003

Recently there is a growing interest in mobile cellular network providing multimedia service. However, the link bandwidth of mobile cellular network is not sufficient enough to provide satisfactory services to users. To overcome this problem, an adaptive framework has been proposed. In this study, we propose a new method of estimating DPR(Degradation Period Ratio) in an adaptive multimedia network where the bandwidth of ongoing call can be dynamically adjusted during its lifetime. DPR is a QoS(Quality of Service) parameter which represents the ratio of allocated bandwidth below a pre-defined target to the whole service time of a call. We improve estimation method of DPR using DTMC(Discrete Time Markov Chain) model by calculate mean degradation period, degradation probability more precisely than in existing studies. Under Threshold CAC(Call Admission Control) algorithm, we present analytically how to guarantee QoS to users and illustrate the method by numerical examples. The proposed method is expected to be used as one of CAC schemes in guaranteeing predefined QoS level of DPR.

• IE interfaces
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• v.9 no.3
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• pp.168-179
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• 1996

Automatic repeated recalling from individual computing equipments such as PC and workstations, to access ATM networks may result in call overload to networks. Call overload causes to waste network resources and fail to meet user call processing QoS requirements. We evaluate two call connection request methods: the back-off recall method(BRM) which makes recall with random waiting time after rejection, and the direct recall method(DRM) which repeats call connection request whenever call request is rejected. We evaluate their performances by simulation and it shows that as the total number of attached terminals to each access node increases, BRM performs better than DRM in terms of the call acceptance level and effective network bandwidth utilization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3176-3183
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• 2011

Traffic and congestion control in the wireless sensor network is an important parameter that decides the throughput and QoS (Quality of Service). This paper proposes a transmission rate priority-based traffic control scheme to serve digital contents streaming in wireless sensor networks. In this paper, priority for transmission rate decides on the real-time traffic and non-real-time with burst time and length. This transmission rate-based priority creates low latency and high reliability so that traffic can be efficiently controlled when needed. Traffic control in this paper performs the service differentiation via traffic detection process, traffic notification process and traffic adjustment. The simulation results show that the proposed scheme achieves improved performance in delay rate, packet loss rate and throughput compared with those of other existing CCF and WCA.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1059-1065
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• 2014

Wind turbine system can obtain the maximum wind energy using torque control under the rated wind speed, and wind turbine power is controlled as the rated power using pitch control over the rated wind speed. In this paper, we present a method for wind turbine pitch controller using neural networks. The purpose of the pitch control is to control generator speed and power in the above rated wind speed. To improve the neural network pitch controller, the difference between a rated and current speed of generator has been used for another input of neural networks as well as wind speed. Error back-propagation algorithm is used for training the neural network pitch controller and simulation and Matlab/Simulink is used for verifying that this system is controlled well.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.389-398
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• 2013

This study aims to support rational security investment decision making through prioritizing on operational level of management measures strategically, in carrying out industrial security activities. For this, AHP survey is conducted against industrial security professionals and analyzed. Thereafter, the importance and the priority of industrial security management measures are determined. As a result, in a comparison evaluation among the criteria, 'ICT service management' represents the highest weight (0.54). And the sub-criteria could be divided into three groups (Group I, II, III), depending on their importance. The sensitivity analysis results show that if the weight of the criterion, 'ICT systems/networks access control' is doubled, the sub-criteria, 'O/S access control', 'application access control', and 'wired/wireless network access control' are enter into top rank group. In case of the criterion, 'physical/environmental security' is doubled, the sub-criteria, 'protection zoning/access control' and 'disaster prevention on business equipment/counter-terrorism' are enter into the top rank group, 'securing utilities' is enter into the mid rank group.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1380-1397
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• 2018

The synchronous reluctance motor (SynRM) servo-drive system has highly nonlinear uncertainties owing to a convex construction effect. It is difficult for the linear control method to achieve good performance for the SynRM drive system. The nonlinear backstepping control system using upper bound with switching function is proposed to inhibit uncertainty action for controlling the SynRM drive system. However, this method uses a large upper bound with a switching function, which results in a large chattering. In order to reduce this chattering, a nonlinear backstepping control system using an adaptive law is proposed to estimate the lumped uncertainty. Since this method uses an adaptive law, it cannot achiever satisfactory performance. Therefore, a nonlinear backstepping control system using a reformed recurrent Hermite polynomial neural network with an adaptive law and an error estimated law is proposed to estimate the lumped uncertainty and to compensate the estimated error in order to enhance the robustness of the SynRM drive system. Further, the reformed recurrent Hermite polynomial neural network with two learning rates is derived according to an increment type Lyapunov function to speed-up the parameter convergence. Finally, some experimental results and a comparative analysis are presented to verify that the proposed control system has better control performance for controlling SynRM drive systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1673-1678
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• 2019

There are various networks and communication methods are used in industrial communication. Enterprises need to convert communications between industrial devices and networks for production line expansion, factory upgrades, network segmentation, and SI. This requires designers manufactured by many manufacturers to provide communication equipment for data or protocol conversion in order to connect and transmit various other mechanical devices to the network. This paper designed industrial communication gateway that can support the transformation of industrial communication protocol using multi-layered communication module. Industrial communication gateways have a structure that connects individual communication modules using RS485 communication to multiple layers. Each communication module consisted of analog and digital data card, LAN, and CAN-enabled card. The main board processor used Atmega micro-processor, and the RS485 slot was placed to have a multi-layer communication module structure. These additive layer type communication modules support analog and digital I/O functions and LAN and CAN for wide use in industrial communication control and monitoring.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.4
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• pp.1-9
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• 2015

This paper proposes CAC method that is more efficient for RRM using game theory combined with Multiple Attribute Decision Making(MADM). Because users request services with different Quality of Service(QoS), the network preference values to alternative networks for each service are calculated by MADM methods such as Grey Relational Analysis(GRA), Simple Additive Weighting(SAW) and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS). According to a utility function representing preference value, non-cooperative game is played, and then network provider select the requested service that provide maximum payoff. The appropriate service is selected through Nash Equilibrium that is the solution of game and the game is played repeated. We analyze two overlaid networks among four Wireless LAN(WLAN) systems with different properties. Simulation results show that proposed MADM techniques have same outcomes for every game round.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1811-1817
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• 2014

In this paper, a PID controller with interpolated gains by use of neural networks is proposed for the formation control problem that following robots track a leading robot with constant distances and angles when there are changes in the mass of the following robot. The whole control system is composed of a kinematic controller and a dynamic controller considering the robot dynamics. The dynamic controller is the PID controller with varying gains, and the proper gains are obtained for some representative masses of the follower robot by the genetic algorithm. Neural networks is trained using the genetic algorithm with the gain data obtained in the previous step. The trained neural network determines optimal PID gains for a random mass of following robot. Simulation studies show that for arbitrary masses of the tracking robot, the PID controller with interpolated gains by the trained neural network has better tracking performance than that of the PID controller with fixed gains.