• Title/Summary/Keyword: simulated network

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Theoretical Study of the Circuits for Device of the High Voltage Pulse Generator (고전압 펄스 발생 장치의 회로에 관한 이론적 연구)

  • Kim, Young-Ju
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.27 no.1
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    • pp.99-108
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    • 2013
  • The high-voltage pulse generator is consist of transformers of fundamental wave and harmonic waves, and shunt capacitances. The pulse has the fundamental wave and the harmonic waves that have been increased as a series circuit by the transformers to make high voltage pulse. This paper shows that pulse generator circuit is analyzed using Miller's theorem and network theory(ABCD Matrix) and simulated in frequency and time domain using Matlab program. The output voltage of pulse were obtained to 2.5kHz, 1.8kV. Output pulse voltage increases as $L_m$ increases in low voltage circuit. In high voltage circuit, outer capacitors are related to frequency band pass characteristics.

Surface EMG Network Analysis and Robotic Arm Control Implementation

  • Ryu, Kwang-Ryol
    • Journal of information and communication convergence engineering
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    • v.9 no.6
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    • pp.743-746
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    • 2011
  • An implementation for surface EMG network analysis and vertical control system of robotic arm is presented in this paper. The transmembranes are simulated by equivalent circuit and cable equation for propagation to be converted to circuit networks. The implementation is realized to be derived from the detecting EMG signal from 3 electrodes, and EMG transmembrane signals of human arm muscles are detected by several surface electrodes, high performance amplifier and filtering, converting analog to digital data and driving a servomotor for spontaneous robotic arm. The system is experimented by monitoring multiple steps vertical control angles corresponding to biceps muscle movement. The experimental results are that the vertical moving control level is measured to around 2 degrees and mean error ranges are lower 5%.

A Flexible Conveying System using Hybrid Control under Distributed Network

  • Yeamglin, Theera;Charoenseang, Siam
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.583-586
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    • 2002
  • In this research, we propose a flexible conveying system (FCS) which consists of multiple arrays of cells. Each cell is a wheel driven by a two degree-of-freedom mechanism. The direction and velocity of cell are controlled based on the concept of hybrid control under a distributed network. Each cell has its own controller under a subsumption architecture for low-level control. A cell communicates with its four neighboring cells to manipulate n targeted object towards its desired position. The high-level control assigns a desired position and direction of the object to each cell. The path of each object is generated by many supporting cells. Moreover, the FCS can handle multiple objects simultaneously. To study the flexible conveying system, a GUI-based simulator of flexible conveying system is constructed. The simulated results show that the system can handle multiple objects independently and simultaneously under the proposed hybrid control architecture.

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A New Binary Frequency Shift Keying Technique Using Cellular Oscillator Networks (셀 룰라 발진기 네트웍을 이용한 새로운 2진 주파수 편이 변조 기법)

  • Won, Eun-Ju;Kang, Sung-Mook;Choi, Jong-Ho;Moon, Gyu
    • Proceedings of the IEEK Conference
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    • 2000.06b
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    • pp.258-261
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    • 2000
  • In this paper, the design of Binary FSK Using Cellular Oscillator Network architecture is newly introduced and analyzed. With its easy frequency controllability and MHz range of quadrature signals, the Cellular Oscillator Network can be used in RF communication systems. Binary Frequency Shift Keying can also be implemented through digital loop-path switching. This FSK model is simulated and proved with typical 3V, 0.5$\mu\textrm{m}$ CMOS N-well process parameters.

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Nonlinear control of structure using neuro-predictive algorithm

  • Baghban, Amir;Karamodin, Abbas;Haji-Kazemi, Hasan
    • Smart Structures and Systems
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    • v.16 no.6
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    • pp.1133-1145
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    • 2015
  • A new neural network (NN) predictive controller (NNPC) algorithm has been developed and tested in the computer simulation of active control of a nonlinear structure. In the present method an NN is used as a predictor. This NN has been trained to predict the future response of the structure to determine the control forces. These control forces are calculated by minimizing the difference between the predicted and desired responses via a numerical minimization algorithm. Since the NNPC is very time consuming and not suitable for real-time control, it is then used to train an NN controller. To consider the effectiveness of the controller on probability of damage, fragility curves are generated. The approach is validated by using simulated response of a 3 story nonlinear benchmark building excited by several historical earthquake records. The simulation results are then compared with a linear quadratic Gaussian (LQG) active controller. The results indicate that the proposed algorithm is completely effective in relative displacement reduction.

Robust On-line Training of Multilayer Perceptrons via Direct Implementation of Variable Structure Systems Theory

  • Topalov, Andon V.;Kaynak, Okyay
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.300-303
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    • 2003
  • An Algorithm based on direct implementation of variable structure systems theory approach is proposed for on-line training of multilayer perceptrons. Network structures which have multiple inputs, single output and one hidden layer are considered and the weights are assumed to have capabilities for continuous time adaptation. The zero level set of the network learning error is regarded as a sliding surface in the learning parameters space. A sliding mode trajectory can be brought on and reached in finite time on such a sliding manifold. Results from simulated on-line identification task for a two-link planar manipulator dynamics are also presented.

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Behavior Analysis of Evolved Neural Network based on Cellular Automata

  • Song, Geum-Beom;Cho, Sung-Bae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.181-184
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    • 1998
  • CAM-Brain is a model to develop neural networks based in cellular automata by evolution, and finally aims at a model as and artificial brain,. In order to show the feasibility of evolutionary engineering to develop an artificial brain we have attempted to evolve a module of CAM-Brain for the problem to control a mobile robot, In this paper, we present some recent results obtained by analyzing the behaviors of the evolved neural module. Several experiments reveal a couple of problems that should be solved when CAM-Brain evolves to control a mobile robot. so that some modification of the original model is proposed to solve them. The modified CAM-Brain has evolved to behave well in a simulated environment, and a thorough analysis proves the power of evolution.

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In Silico Analysis of Lactic Acid Secretion Metabolism through the Top-down Approach: Effect of Grouping in Enzyme kinetics

  • Jin, Jong-Hwa;Lee, Jin-Won
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.10 no.5
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    • pp.462-469
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    • 2005
  • A top-down approach is known to be a useful and effective technique for the design and analysis of metabolic systems. In this Study, we have constructed a grouped metabolic network for Lactococcus lactis under aerobic conditions using grouped enzyme kinetics. To test the usefulness of grouping work, a non-grouped system and grouped systems were compared quantitatively with each other. Here, grouped Systems were designed as two groups according to the extent of grouping. The overall simulated flux values in grouped and non-grouped models had pretty similar distribution trends, but the details on flux ratio at the pyruvate branch point showed a little difference. This result indicates that our grouping technique can be used as a good model for complicated metabolic networks, however, for detailed analysis of metabolic network, a more robust mechanism Should be considered. In addition to the data for the pyruvate branch point analysis, Some major flux control coefficients were obtained in this research.

Design and Implementation of On-board Computers for KAISTSAT-4 (과학위성 1호 탑재 컴퓨터의 설계 및 구현)

  • 곽성우;류상문;박홍영;오대수;유관호;최병재;김병국
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.31 no.4
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    • pp.105-111
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    • 2003
  • Qualification Model of On-board Computer (OBC) for KAISTSAT-4 was developed. The OBC of KAISTASAT-4 has some improved features compared with that of KAISTSAT-3: To reduce weight and size of OBC many logics are implemented by FPGAs, and a network controller is included in OBC to access the satellite network with high speed. Also, the developed OBC has an improved tolerance against SEUs and faults. The OBC was fully tested under simulated space environment with no errors.

A Dependability Estimation of Microprocessor-based Software under Memory Faults using Stochastic Activity Network (SAN)

  • Park, Jong-Gyun;Seong, Poong-Hyun
    • Proceedings of the Korean Nuclear Society Conference
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    • 1996.05b
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    • pp.725-730
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    • 1996
  • In this work, the software behavior under memory faults in operation phase is modeled and simulated using the stochastic activity network, generalized stochastic Petri nets. This networks permit the representation of concurrency, timeliness, fault tolerance, and degradable performance of system and provide a means for determining the stochastic behavior of a complex system. We estimate the reliability of an application software in the digitized system in nuclear power plants and show the sensitivity of the software reliability to the major physical parameters which affect the software failure in normal operation phase. We found that the effects of the hardware faults on the software failure should be considered for predicting the software dependability accurately in operation phase.

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