• Title/Summary/Keyword: Output Estimation

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Speed Control of Three Phase Slotless PM BLDC Motor Using Single Sensor (Single Sensor를 이용한 3상 슬롯리스 PM BLDC 전동기의 속도제어)

  • Yoon Y. H.;Kim Y. C.;Lee S. S.;Won C. Y.;Choe Y. Y.
    • The Transactions of the Korean Institute of Power Electronics
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    • v.9 no.6
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    • pp.536-543
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    • 2004
  • Slotless Permanent Magnet Brushless DC Motor(PM BLDC) with the characteristics of high speed and power density has been more widely used In Industrial and factory machine. Generally, PM BLDC meter is necessary that the three Hall-lCs evenly be distributed around the stator circumference in case of the 3 phase motor. The Hall-ICs are set up in PM BLDC Motor to detect the main flux from the rotor. therefore the output signal from Hall-ICs is used to drive a power transistor to control the stator winding current. However, instead of using three Hall-ICs, if it used only one Hall-IC, we can estimate information of the others phase in sequence through a rotor This paper identified the characteristics and performance by using one Hall-IC with the 3-phase, 2-pole, 6-slot PM BLDC motor.

Design and Performance Gain Evaluation of a Multi-Rank Codebook Utilizing Statistical Properties of the Spatial Channel Model (공간 채널 모델의 통계적 특성을 반영한 다중 랭크 코드북의 설계 및 성능 이득 평가)

  • Kim, Changhyeon;Sung, Wonjin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.7
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    • pp.723-731
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    • 2016
  • A core technological base to provide enhanced data rates required by 5G mobile wireless communications is the improved bandwidth efficiency using massive multiple-input multiple-output (MIMO) transmission. MIMO transmission requires the channel estimation using the channel state information reference signaling (CSI-RS) and appropriate beamforming, thus the design of the codebook defining proper beamforming vectors is an important issue. In this paper, we propose a multi-rank codebook based on the discrete Fourier transform (DFT) matrix, by utilizing statistical properties of the channel generated by the spatial channel model (SCM). The proposed method includes a structural change of the precoding matrix indicator (PMI) by considering the phase difference distributions between adjacent antenna elements, as well as the selected codevector characteristics of each transmission layer. Performance gain of the proposed method is evaluated and verified by making the performance comparison to the 3GPP standard codebooks adopted by Long-Term Evolution (LTE) systems.

Estimation of Kinetic Coefficient and Assimilated Nutrients Mass in SBR Process (연속회분식 반응 공정에서 동역학적 계수 및 미생물합성에 사용된 영양물질 산정)

  • Ji, Dae-Hyun;Shin, Sang-Woo;Lee, Kwang-Ho;Lee, Jae-Kune
    • Journal of Korean Society on Water Environment
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    • v.23 no.5
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    • pp.607-612
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    • 2007
  • In this study, we investigated the variations of the kinetic coefficients and Chemical Oxygen Demand (COD), N and P mass used for assimilation of a sequencing batch reactor (SBR) system with the variation of SRTs; SRTs of 7.5, 10.0, 12.5, 15.0 and 20.0 days were tested in one cycle of SBR operation to determine the optimum conditions for the operation of the SBR and estimate its COD, nitrogen and phosphorus removal efficiencies. The SBR system was operated under the conditions as follows: an operation time of 6 hours per cycle, a hydraulic retention time (HRT) of 12 hours, an influent COD loading of $0.4kg/m^3/day$, and an influent nitrogen loading of $0.068kgT-N/m^3/day$. The yield coefficient (Y) and decay rate coefficient ($k_d$) were estimated to be 0.4198 kgMLVSS/kgCOD and $0.0107day^{-1}$ by calculating the removal rate of substrate according to the variation of SRT. Considering total nitrogen amount removed by sludge waste process, eliminated by denitrification, and in clarified water effluent with reference to 150 mg/cycle of influent nitrogen amount, the percentage of nitrogen mass balance from the ratio of the nitrogen amount in effluent (N output) to that in influent (N input) for Runs 1~5 were 95.5, 97.0, 95.5, 99.5, and 95.5%, respectively, which is well accounted for, with mass balances close to 100%.

Design of a Direct Self-tuning Controller Using Neural Network (신경회로망을 이용한 직접 자기동조제어기의 설계)

  • 조원철;이인수
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.40 no.4
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    • pp.264-274
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    • 2003
  • This paper presents a direct generalized minimum-variance self tuning controller with a PID structure using neural network which adapts to the changing parameters of the nonlinear system with nonminimum phase behavior, noises and time delays. The self-tuning controller with a PID structure is a combination of the simple structure of a PID controller and the characteristics of a self-tuning controller that can adapt to changes in the environment. The self-tuning control effect is achieved through the RLS (recursive least square) algorithm at the parameter estimation stage as well as through the Robbins-Monro algorithm at the stage of optimizing the design parameter of the controller. The neural network control effect which compensates for nonlinear factor is obtained from the learning algorithm which the learning error between the filtered reference and the auxiliary output of plant becomes zero. Computer simulation has shown that the proposed method works effectively on the nonlinear nonminimum phase system with time delays and changed system parameter.

The Analysis of View and Daylights for the Design of Public Housing Complexes Using a Residential Environment Analysis System Integrated into a CAD System (주거환경분석시스템의 CAD 시스템 통합을 통한 공동주택단지설계 시 일조 및 조망분석에 관한 연구)

  • Park, Soo-Hoon;Ryu, Jeong-Won
    • Korean Journal of Computational Design and Engineering
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    • v.12 no.2
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    • pp.137-145
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    • 2007
  • This paper concerns about residential environment analysis program implementation for design and analysis on public housing complexes such that view and daylight analysis processes are automated and integrated into existing design routine to achieve better design efficiency. Considering the architectural design trends this paper chooses ArchiCAD as a platform for a CAD system, which contains the concepts such as integrated object-oriented CAD, virtual building and BIM. Residential environment analysis system consists of three components. The first component is the 3D modeling part defining 3D form information for external geographic contour models, site models and interior/exterior of apartment buildings. The second is the parametric library part handling the design parameters for view and daylight analysis. The last is the user interface for the input/output and integration of data for the environment analysis. Daylight analysis shows rendered images as well as results of daylight reports and grades per time and performs the calculations for floor shadow. It separates the site-only analysis from the analysis of site and exterior environmental parameters. View analysis considers horizontal and vertical view angles to produce view image from each unit and uses the bitmap analysis method to determine opening ratio, scenery ratio and void ratio. We could expect better performance and precision from this residential environment analysis system than the existing 2D drawing based view and daylight analysis methods and overcome the existing one-way flow of design information from 3D form to analysis reports so that site design modifications are automatically reflected on analysis results. Each part is developed in a module so that further integration and extension into other related estimation and construction management systems are made possible.

The Estimation and Change in the Number of Employed Persons Related to Agriculture in Agribusiness, 1995-2000-2005 (농업관련산업의 농업관련 취업자수의 추계 및 그 변화 1995-2000-2005)

  • Lee, Jong-Sang
    • Journal of Agricultural Extension & Community Development
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    • v.17 no.1
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    • pp.25-43
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    • 2010
  • The objectives of this study are to estimate the number of employed persons related to agriculture in agribusiness, to determine any factors affecting changes in employed persons, based on the Input-Output Tables in 1995, 2000, and 2005. The number of employed persons related to Crops in the input industry of agriculture was 184,076 in 1995, 186,616 in 2000, and 193,394 in 2005. The sectors with higher number of employed persons were in; Agriculture, forestry and fishing related services, Wholesale and retail trade, Fertilizers and agricultural chemicals, and Forest products, etc. The number of employed persons related to Animals in the input industry of agriculture was 46,6166 in 1995, 28,886 in 2000, and 35,714 in 2005. The sectors with higher number of employed persons were in; Wholesale and retail trade, Prepared livestock feeds, Agriculture, forestry and fishing related services, and Forest products, etc. The number of employed persons related to Crops in post-farm gate industries was 184,076 in 1995, 186,616 in 2000, and 193,394 in 2005. The sectors with higher number of employed persons were in; Accommodation and food services, Other food products, Wholesale and retail trade, and Polished grains, flour and milled cereals, etc. The number of employed persons related to Animals in the post-farm gate industries was 184,076 in 1995, 186,616 in 2000, and 193,394 in 2005. The sectors with higher number of employed persons were in; Meat and dairy products, Wholesale and retail trade, Accommodation and food services, and Land transport, etc. In 2005, the number of employed persons related to agriculture in agribusiness per 1,000 employed persons in agriculture was 211, in the input industries in agriculture it was 53, and in the post-farm gate industries it was 158.gribusiness.

Improving the Performance of the Capon Algorithm by Nulling Elements of an Inverse Covariance Matrix (공분산 역행렬 원소 제거 기법을 이용한 Capon 알고리듬의 성능 개선)

  • Kim, Seong-Min;Kang, Dong-Hoon;Lee, Yong-Wook;Nah, Sun-Phil;Oh, Wang-Rok
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.5
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    • pp.96-101
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    • 2011
  • It is well known that the Capon algorithm offers better resolution compared to that of the FM (Fourier method) algorithm by minimizing the total output power while maintaining a constant gain in the look direction. Unfortunately, the DoA (Direction of Arrival) estimation performance of the Capon algorithm is drastically degraded when the SNR of received signal is low and thus, it cannot distinguish among signal sources which have similar incidence angles. In this paper, we propose a novel scheme enhancing the resolution of the Capon algorithm by ing all rows except the first row of an inverse covariance matrix.

Damage Detection of Building Structures Using Ambient Vibration Measuresent (자연진동을 이용한 건물의 건전도 평가)

  • Kim, Sang Yun;Kwon, Dae Hong;Yoo, Suk Hyeong;Noh, Sam Young;Shin, Sung Woo
    • KIEAE Journal
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    • v.7 no.4
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    • pp.147-152
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    • 2007
  • Numerous non-destructive tests(NDT) to assess the safety of real structures have been developed. System identification(SI) techniques using dynamic responses and behaviors of structural systems become an outstanding issue of researchers. However the conventional SI techniques are identified to be non-practical to the complex and tall buildings, due to limitation of the availability of an accurate data that is magnitude or location of external loads. In most SI approaches, the information on input loading and output responses must be known. In many cases, measuring the input information may take most of the resources, and it is very difficult to accurately measure the input information during actual vibrations of practical importance, e.g., earthquakes, winds, micro seismic tremors, and mechanical vibration. However, the desirability and application potential of SI to real structures could be highly improved if an algorithm is available that can estimate structural parameters based on the response data alone without the input information. Thus a technique to estimate structural properties of building without input measurement data and using limited response is essential in structural health monitoring. In this study, shaking table tests on three-story plane frame steel structures were performed. Out-put only model analysis on the measured data was performed, and the dynamic properties were inverse analyzed using least square method in time domain. In results damage detection was performed in each member level, which was performed at story level in conventional SI techniques of frequency domain.

Multi-focus Image Fusion Technique Based on Parzen-windows Estimates (Parzen 윈도우 추정에 기반한 다중 초점 이미지 융합 기법)

  • Atole, Ronnel R.;Park, Daechul
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.8 no.4
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    • pp.75-88
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    • 2008
  • This paper presents a spatial-level nonparametric multi-focus image fusion technique based on kernel estimates of input image blocks' underlying class-conditional probability density functions. Image fusion is approached as a classification task whose posterior class probabilities, P($wi{\mid}Bikl$), are calculated with likelihood density functions that are estimated from the training patterns. For each of the C input images Ii, the proposed method defines i classes wi and forms the fused image Z(k,l) from a decision map represented by a set of $P{\times}Q$ blocks Bikl whose features maximize the discriminant function based on the Bayesian decision principle. Performance of the proposed technique is evaluated in terms of RMSE and Mutual Information (MI) as the output quality measures. The width of the kernel functions, ${\sigma}$, were made to vary, and different kernels and block sizes were applied in performance evaluation. The proposed scheme is tested with C=2 and C=3 input images and results exhibited good performance.

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Neuro-Fuzzy Modeling based on Self-Organizing Clustering (자기구성 클러스터링 기반 뉴로-퍼지 모델링)

  • Kim Sung-Suk;Ryu Jeong-Woong;Kim Yong-Tae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.6
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    • pp.688-694
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    • 2005
  • In this Paper, we Propose a new neuro-fuzzy modeling using clustering-based learning method. In the proposed clustering method, number of clusters is automatically inferred and its parameters are optimized simultaneously, Also, a neuro-fuzzy model is learned based on clustering information at same time. In the previous modelling method, clustering and model learning are performed independently and have no exchange of its informations. However, in the proposed method, overall neuro-fuzzy model is generated by using both clustering and model learning, and the information of modelling output is used to clustering of input. The proposed method improve the computational load of modeling using Subtractive clustering method. Simulation results show that the proposed method has an effectiveness compared with the previous methods.