• Title/Summary/Keyword: Actual network

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Sensorless Control of Induction Motor Using Fuzzy-Neural Network (퍼지-신경회로망을 이용한 유도전동기의 센서리스 제어)

  • Nam, Su-Myeong;Lee, Jung-Chul;Lee, Hong-Gyun;Lee, Young-Sil;Chung, Dong-Hwa
    • Proceedings of the KIEE Conference
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    • 2004.04a
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    • pp.177-180
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    • 2004
  • This paper is proposed a fuzzy neural network controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed estimation and control of speed of induction motor using ANN Controller. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

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Proposal of Virtual Sensor Technique for Quadruped Robot using Backpropagation Neural Network (Back propagation 신경망이론을 이용한 4 족 보행로봇의 가상 센서 기술 제안)

  • Kim, Wan-Soo;Yu, Seung-Nam;Han, Chang-Soo
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.894-899
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    • 2008
  • Measured sensor datum from a quadruped robotics is commonly used for recognizing physical environment information which controls the posture of robotics. We can advance the ambulation with this sensed information and need to synthesize various sensors for obtaining accurate data, but most of these sensors are expensive and require excessive load for the operation. Those defects can be serious problem when it comes to the prototype's practicality and mass production, and maintenance of the system. This paper suggests virtual sensor technology for avoiding previous defects and presents ways to apply a theory to a walking robotics through virtual sensor information which is trained with several kinds of actual sensor information from the prototype system; the general algorithm is initially based on the neural network theory of back propagation. In specific, we verified a possibility of replacing the virtual sensor with the actual one through a reaction force measurement experiment.

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Latency Analysis of AVB Network and Optimization Design for Automotive

  • An, Byoungman;Kim, YoungSeop
    • Journal of the Semiconductor & Display Technology
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    • v.18 no.3
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    • pp.127-132
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    • 2019
  • This paper presents an overview of automotive communication technologies, including related technology developments. We describe the latency of Audio Video Bridge (AVB) network as well as purpose the optimized design of the Ethernet network system for automotive. Our design plays a significant role in reducing the delay between components. The proposed approach on realistic test cases showed that there was a delay reduction, approximately 49.4%. It is expected that the optimization method for the actual automotive environment can greatly shorten the time period in the design and development process. The results obtained from the experiments on the delay time present in each function are reliable because average values are obtained through repeated actual tests for several months. It will greatly benefit the industry since analyzing the latency between each function in a short period of time is very important.

Developing Predictive Modelling of CO2 Emissions of Construction Equipment Using Artificial Neural Network and Non-linear Regression (인공신경망 및 비선형 회귀분석을 이용한 건설장비의 CO2 배출량 예측 모델 개발)

  • Im, Somin;Noh, Jaeyun;Ro, Sangwoo;Lee, Minwoo;Han, Seungwoo
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2019.11a
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    • pp.16-17
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    • 2019
  • In order to measure the amount of carbon dioxide emitted from the construction sites, many literature which have been conducted have proposed methodologies for calculating coefficients based on actual data collections for estimating the emission formula. The existing data collected under controlled conditions not on site measurement were too limited to apply in actual sites. The purpose of this study is to conduct analysis based on the data measured in fields and to present predictive models using artificial neural network and nonlinear regression analysis for appropriate predictions and practical applications.

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Estimation and Control of Speed of Induction Motor using FNN and ANN (FNN과 ANN을 이용한 유도전동기의 속도 제어 및 추정)

  • Lee Jung-Chul;Park Gi-Tae;Chung Dong-Hwa
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.42 no.6
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    • pp.77-82
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    • 2005
  • This paper is proposed fuzzy neural network(FNN) and artificial neural network(ANN) based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed control and estimation of speed of induction motor using fuzzy and neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the experimental results to verify the effectiveness of the new method.

Sensorless Vector Control of Induction Motor by Artificial Neural Network (인공 신경망에 의한 유도전동기의 센서리스 벡터제어)

  • Jung, Byung-Jin;Ko, Jae-Sub;Choi, Jung-Sik;Kim, Do-Yeon;Park, Ki-Tae;Choi, Jung-Hoon;Chung, Dong-Hwa
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2007.11a
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    • pp.307-312
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    • 2007
  • The paper is proposed artificial neural network(ANN) sensorless control of induction motor drive with fuzzy learning control-fuzzy neural network(FLC-FNN) controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of induction motor using FLC-FNN and estimation of speed using ANN controller The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The proposed control algorithm is applied to induction motor drive system controlled FLC-FNN and ANN controller, Also, this paper is proposed the analysis results to verify the effectiveness of the FLC-FNN and ANN controller.

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짝비교 기법을 활용한 보조지하수관측망 위치선정 기준 수립에 관한 연구

  • 김정우;김규법;원종호;이진용;이명재;이강근
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2003.04a
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    • pp.259-262
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    • 2003
  • In the Republic of Korea, Ministry of Construction & Transportation and Korea Water Resources Corporation manage the national groundwater monitoring network at the 169 stations and will organize the supplementary groundwater monitoring network at the 10,000 stations by 2011 year. The method that organizes the monitoring network was developed using the Analytic Hierarchy Process with pairwise comparison. Several estimation factors for the estimating every district were selected to reflect each district conditions. Their weighting value was decided by pairwise comparison and questions to the experts about groundwater The optimal number of groundwater monitoring well was calculated through the developed method. To verify this method, groundwater was monitored in Jeonju city by way showing the example. The study area In Jeonju city needs 7 stations for the supplementary groundwater monitoring network. The results monitored in 7 stations inferred the groundwater level around the study area by Kriging. The mean of residual between inferred groundwater level value from Kriging and actual groundwater level is rather low. Furthermore, the mean and standard deviation of residual between inferred groundwater level change and actual groundwater change is much lower. The Fact that 7 monitoring stations are sufficient for observing the groundwater condition in the study area makes it possible for suggested monitoring number to be proper.

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Applicability of Several Skeletonization Methods for the Transient Analysis in the Water Distribution System (상수관망 부정류 해석을 위한 관망 간략화 방법에 대한 연구)

  • Lee, Jong-Pil;Kim, Hyung-Guen;Kim, Sang-Hyun;Lee, Hyun-Dong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.521-526
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    • 2004
  • It is necessary to analyze the unsteady flow in the pipe network for the better operation and controls, but there are some problems in actual pipe network simulation, such as collecting a large amount of information in the field, operating highly upgraded computer system, and keeping a big storage device to run analysis program. The skeletonization method is used to cope with the problems in this paper. It is expected to reduce computation time, researcher's efforts, and costs for the analyzing the pipe network. The impact of individual pipe elements to the behavior of the water distribution system can be accounted in the process of skeletonization. However it is also important to study continuously about how to apply the skeletonization method for each of different cases, because inadequate uses may bring simulation to a false result. This paper introduces basic theories and skeletonizing examples in the actual pipe network in Dae-gu city.

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An Application and Evaluation of Hub-and-spoke Strategy for Rail Freight Service in European Networks (철도화물서비스를 위한 Hub-and-spoke 운송전략의 적용과 평가: 유럽 사례를 중심으로)

  • 정승주
    • Journal of the Korean Society for Railway
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    • v.7 no.3
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    • pp.264-270
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    • 2004
  • The hub-and-spoke strategy is widely used in the field of transportation. At the field of rail transportation, however, it is difficult that we find an application case of this strategy because of modal characteristics. According to the fast growth of containerization and the development of transshipment technology, presently, the hub-and-spoke strategy is introduced by operators on actual European rail freight transportation. However, it is hardly to find empirical studies evaluating the applicability of transportation strategy. In this context, this study analyzed the applicabilities of hub-and-spoke strategy in the actual network of European rail freight. For the application and evaluation of the characteristics of hub-and-spoke strategy, it utilized a service network design model for rail freight. Utilizing this model, it analyzed the efficiency of furnished rail freight services, the potential locations of hubs, the characteristics of O-D flows by the types of trains and service links, and the types of paths of O-D flows. Finally, it proposed some implications and the further study topics.

ANN Sensorless Control of Induction Motor Drive with AFNN (AFNN 제어기에 의한 유도전동기 드라이브의 ANN 센서리스 제어)

  • Ko, Jae-Sub;Nam, Su-Myeong;Choi, Jung-Sik;Park, Bung-Sang;Chung, Dong-Hwa
    • Proceedings of the KIEE Conference
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    • 2005.10c
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    • pp.195-197
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    • 2005
  • This paper is proposed adaptive fuzzy neural network(AFNN) and artificial neural network(ANN) based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed control and estimation of speed of induction motor using fuzzy and neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed. so that the actual state variable will coincide with the desired one. This paper is proposed the experimental results to verify the effectiveness of the new method.

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