• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1372-1377
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• 2013

In this Paper, a back propagation neural network learning algorithm based on the complex multilayer perceptron is represented for controling and detecting interference of the received signals in cellular mobile communication system. We proposed neural network adaptive correlator which has fast convergence rate and good performance with combining back propagation neural network and the receiver of cellular. We analyzed and proved that NNAC has lower bit error probability than that of traditional RAKE receiver through results of computer simulation in the presence of the tone and narrow-band interference and the co-channel interference.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.87-98
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• 1990

The performance analysis and capacity planning of Service Control Point which is real time response system is studied. The system is modeled by multiclass open queueing network. The analytical method is used to solve the queueing network. The solution of the model has product form solution. The focus of this paper is to investigate the capacity of system under the restriction of response time. To get the reasonable capacities, nonlinear programming problem is formulated and is solved by GINO. And the simulation model using SLAM II is formulated.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.3
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• pp.319-330
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• 2002

We consider BMAP/G/1 queueing system with N-policy and multiple vacations. We derive the vector generating functions of the queue length in a factorized form and interpret the factorization. We also derive the mean queue length.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1346-1349
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• 1993

In this paper, we describe the use of certain optimization techniques, principally dynamic programming and high level computational methods, to enhance the capabilities of a fuzzy adaptive neural network controller which we had developed for on-line control and adaption on complex nonlinear processes. Potential applications to an array of processes from diverse fields are discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.5
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• pp.291-295
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• 2014

This paper presents the implementation of industrial wireless network for real-time control system and the performance evaluation on the implemented system. We propose the hybrid network architecture of wired EtherCAT and wireless 802.15.4e. For performance evaluation, we use the reference model of inverse pendulum system. Through the performance evaluation on our testbed system, it is verified that our proposed system can be applied to industrial real-time control system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.93-96
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• 1997

The paper suggests a guide of designing and implementing automation systems using industrial communication networks.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.301-303
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• 2000

This paper presents Kohonen neural network and wavelet transform analysis based technique for industrial peak load forecasting for the purpose of peak demand control. Firstly, one year of historical load data were sorted and clustered into several groups using Kohonen neural network and then wavelet transforms are adopted using the Biorthogonal mother wavelet in order to forecast the peak load of one hour ahead. The 5-level decomposition of the daily industrial load curve is implemented to consider the weather sensitive component of loads effectively. The wavelet coefficients associated with certain frequency and time localization is adjusted using the conventional multiple regression method and the components are reconstructed to predict the final loads through a six-scale synthesis technique.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.598-601
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• 2001

As many sensors and actuators are used in many automated system, various industrial networks are adopted for digital control system. In order to take advantages of the networking, however, the network implementation should be carefully designed to satisfy real-time requirements considering network delays. This paper presents the implementation scheme of a networked control system via Profibus-DP network. More specifically, the effect of the network delay on the control performance was evaluated on a Profibus-DP testbed, and a GA based PID tuning algorithm is proposed to demonstrate the fesibility of the networked control system.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.3
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• pp.65-70
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• 2001

This Paper Propose the control chart Pattern to provide a more comprehensive scheme for detecting process shifts using individual observations in start-up process. In this paper, which uses the backpropagation algorithm two samples are fed into the trained neural network to provide outputs ranging from 0 to 1. The main advantage of using neural networks approach with a control chart is that the neural network has almost no delay in detecting small shift. This paper illustrates how neural networks can provide a useful method for optimizing parameter(connection weights) that affect process control. Simulation results show that the performance of the proposed control chart using the neural network (NNCC) is quite promising.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2634-2638
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• 2009

The variable structure control(VSC) with sliding mode is the discontinuous control law in leads to undesirable chattering in practice. As a method solving this problem, in this paper, we propose a scheme of the VSC with neural network sliding surface. A neural network sliding surface with boundary layer is employed to solve discontinuous control law. The proposed controller can eliminate the chattering problem of the conventional VSC. The effectiveness of the proposed control scheme is verified by simulation results.