• 제목/요약/키워드: Least Squares Algorithm

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무선 센서네트워크에서의 시각동기를 위한 실시간 클럭 스큐 추정 (Realtime Clock Skew Estimator for Time Synchronization in Wireless Sensor Networks of WUSB and WBAN)

  • 허경
    • 한국멀티미디어학회논문지
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    • 제15권11호
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    • pp.1391-1398
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    • 2012
  • 무선 센서네트워크에서의 시각동기는 Wireless USB, WBAN 등의 MAC 계층에서부터 응용 계층에 이르기까지 거의 모든 계층에서 다양한 목적을 위해 매우 중요한 기술이다. 본 논문에서는 무선 센서네트워크에서의 시각동기를 위한 실시간 클럭 스큐 추정 방법을 제시한다. 재귀적 최소제곱법을 통해 오프셋 보정 정보들을 얻을 때마다 클럭 스큐가 실시간적으로 추정 및 갱신되며, 아울러 스큐 추정을 위해 각 센서노드에 저장해야할 정보를 최소화한다. 제안한 클럭 스큐 추정 방법은 기존의 클럭 오프셋 보정 방법과 쉽게 통합될 수 있으며, 이 경우 보다 정확하고 효율적인 시각동기화가 가능해진다. 시뮬레이션 및 실험 결과를 통해 제안한 클럭 스큐 추정 방법을 통한 시각동기 정확도의 향상을 보인다.

이동로봇의 경로추적을 위한 2-입력 2-출력 ANFIS제어기 (2-Input 2-Output ANFIS Controller for Trajectory Tracking of Mobile Robot)

  • 이홍규
    • 한국항행학회논문지
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    • 제16권4호
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    • pp.586-592
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    • 2012
  • 비선형 시스템을 제어하는 효과적인 방법으로 신경망과 연동된 퍼지구조를 적용한 ANFIS 제어기를 이용되고 있다. 전통적인 ANFIS에서는 다차원의 입력에도 불구하고 단일출력에 대한 공정을 모델링하고 제어 하는데 사용된다. 멤버쉽 함수의 파라미터는 최소자승예측과 역전파 알고리즘을 이용하여 조정된다. 이동로봇의 경우에는 좌측과 우측의 바퀴를 각각 구동할 필요가 있다. 본 논문에서는 이동로봇의 궤적을 추적하기 위하여 2-입력 2-출력을 가진 ANFIS제어기를 적용한 제어시스템 구조를 제안하였다. 시뮬레이션을 통하여 제안된 구조가 이동로봇에 대한 가능한 제어기임을 확인할 수 있었다.

다이아몬드 터닝 머시인의 극초정밀 절삭공정에서의 시스템 규명 및 제어 (System identification and admittance model-based nanodynamic control of ultra-precision cutting process)

  • 정상화;김상석;오용훈
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.1352-1355
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    • 1996
  • The control of diamond turning is usually achieved through a laser-interferometer feedback of slide position. If the tool post is rigid and the material removal process is relatively static, then such a non-collocated position feedback control scheme may surface. However, as the accuracy requirement gets tighter and desired surface contours become more complex, the need for a direct tool-tip sensing becomes inevitable. The physical constraints of the machining process prohibit any reasonable implementation of a tool-tip motion measurement. It is proposed that the measured force normal to the face of the workpiece can be filtered through an appropriate admittance transfer function to result in the estimated depth of cut. This can be compared to the desired depth of cut to generate the adjustment control action in addition to position feedback control. In this work, the design methodology on the admittance model-based control with a conventional controller is presented. The recursive least-squares algorithm with forgetting factor is proposed to identify the parameters and update the cutting process in real time. The normal cutting forces are measured to identify the cutting dynamics in the real diamond turning process using the precision dynamometer. Based on the parameter estimation of cutting dynamics and the admittance model-based nanodynamic control scheme, simulation results are shown.

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PARP-1 억제제의 Docking 및 QSAR 연구 (Docking and QSAR studies of PARP-1 Inhibitors)

  • Kim, Hye-Jung;Cho, Seung-Joo
    • 한국생물정보학회:학술대회논문집
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    • 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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    • pp.210-218
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    • 2004
  • Poly(ADP-ribose)polymerase-1 (PARP-1) is a nuclear enzyme involved in various physical functions related to genomic repair, and PARP inhibitors have therapeutic application in a variety of neurological diseases. Docking and the QSAR (quantitative structure-activity relationships) studies for 52 PARP-1 inhibitors were conducted using FlexX algorithm, comparative molecular field analysis (CoMFA), and hologram quantitative structure-activity relationship analysis (HQSAR). The resultant FlexX model showed a reasonable correlation (r$^{2}$ = 0.701) between predicted activity and observed activity. Partial least squares analysis produced statistically significant models with q$^{2}$ values of 0.795 (SDEP=0.690, r$^{2}$=0.940, s=0.367) and 0.796 (SDEP=0.678, r$^{2}$ = 0.919, s=0.427) for CoMFA and HQSAR, respectively. The models for the entire inhibitor set were validated by prediction test and scrambling in both QSAR methods. In this work, combination of docking, CoMFA with 3D descriptors and HQSAR based on molecular fragments provided an improved understanding in the interaction between the inhibitors and the PARP. This can be utilized for virtual screening to design novel PARP-1 inhibitors.

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WAVE 시스템에서 선택 다이버시티를 위한 선택 기준에 대한 연구 (A Study on Selection Criterions for Selection Diversity in WAVE Systems)

  • 홍대기
    • 반도체디스플레이기술학회지
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    • 제14권2호
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    • pp.9-16
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    • 2015
  • In this paper, selection criterions on selection diversity are researched. The diversity is applied to the multiple antenna system based on wireless access in vehicular environment (WAVE) standard for rapid varying channel. Least squares (LS) based decision feedback equalizer (DFE) are used for channel equalization. Received signal is regenerated by means of the decision feedback path. In the selection diversity, the regenerated signal as well as the received signal is selected according to selection criterion. The decision feedback algorithm can follow the fast speed of WAVE fading channel. To control the tracking speed of the time-varying channel, simple low pass filter is used. Finally, the estimated channel value recovers the distorted payloads. Signal power before automatic gain control (AGC) in analog stage can be used as a selection criterion. In the digital stage, signal power after AGC, noise power after AGC, signal to noise ratio after AGC and cross-correlation method can be used as selection criterions. According to the simulation results, the performance of the selection diversity is improved in comparison with that of the combining diversity for the WAVE fading channel.

일반화된 예측제어에 의한 가압경수형 원자로의 부하추종 출력제어에 관한 연구 (Generalized predictive control of P.W.R. nuclear power plant)

  • 천희영;박귀태;이종렬;박영환
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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    • pp.663-668
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    • 1990
  • This paper deals with the application of a Generalized Predictive Control (CPC) to a Pressurized Water Reactor (P.W.R) Nuclear Power Plant. Generalized Predictive Control is a sort of Explicit Self-Tuning Control. Current self-tuning algorithms lack robustness to prior choices of either dead-time (input time delay of a plant) or model order. GPC is shown by simulation studies to be superior to accepted self-tuning techniques such as minimum variance and pole-placement from the viewpoint that it is robust to prior choices of dead-time or model order. In this paper a GPC controller is designed to control the P.W.R. nuclear power rlant with varying dead-time and through the designing procedure the designer is free from the constraint of knowing the exact dead-time. The controller is constructed based on the 2nd order linear model approximated in the vicinity of operating point. To ensure that this low-order model describes the complex real dynamics well enough for control purposes, model parameters are updated on-line with a Recursive Least Squares algorithm. Simulation results are successful and show the possibilities of the GPC control application to actual plants with varying or unknown dead-time.

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데이터 전처리를 이용한 다중 모델 퍼지 예측기의 설계 및 응용 (Design of Multiple Model Fuzzy Predictors using Data Preprocessing and its Application)

  • 방영근;이철희
    • 전기학회논문지
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    • 제58권1호
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    • pp.173-180
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    • 2009
  • It is difficult to predict non-stationary or chaotic time series which includes the drift and/or the non-linearity as well as uncertainty. To solve it, we propose an effective prediction method which adopts data preprocessing and multiple model TS fuzzy predictors combined with model selection mechanism. In data preprocessing procedure, the candidates of the optimal difference interval are determined based on the correlation analysis, and corresponding difference data sets are generated in order to use them as predictor input instead of the original ones because the difference data can stabilize the statistical characteristics of those time series and better reveals their implicit properties. Then, TS fuzzy predictors are constructed for multiple model bank, where k-means clustering algorithm is used for fuzzy partition of input space, and the least squares method is applied to parameter identification of fuzzy rules. Among the predictors in the model bank, the one which best minimizes the performance index is selected, and it is used for prediction thereafter. Finally, the error compensation procedure based on correlation analysis is added to improve the prediction accuracy. Some computer simulations are performed to verify the effectiveness of the proposed method.

수정된 비용함수를 이용한 비선형 최적화 방법 기반의 이동로봇의 장애물 회피 비주얼 서보잉 (Visual Servoing of a Wheeled Mobile Robot with the Obstacle Avoidance based on the Nonlinear Optimization using the Modified Cost Function)

  • 김곤우
    • 전기학회논문지
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    • 제58권12호
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    • pp.2498-2504
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    • 2009
  • The fundamental research for the mobile robot navigation using the numerical optimization method is presented. We propose an image-based visual servo navigation algorithm for a wheeled mobile robot utilizing a ceiling mounted camera. For the image-based visual servoing, we define the composite image Jacobian which represents the relationship between the speed of wheels of a mobile robot and the robot's overall speed in the image plane. The rotational speed of wheels of a mobile robot can be directly related to the overall speed of a mobile robot in the image plane using the composite image Jacobian. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the cost function with the image error between the goal position and the position of a mobile robot. In order to avoid the obstacle, the modified cost function is proposed which is composed of the image error between the position of a mobile robot and the goal position and the distance between the position of a mobile robot and the position of the obstacle. The performance was evaluated using the simulation.

Damping of Inter-Area Low Frequency Oscillation Using an Adaptive Wide-Area Damping Controller

  • Yao, Wei;Jiang, L.;Fang, Jiakun;Wen, Jinyu;Wang, Shaorong
    • Journal of Electrical Engineering and Technology
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    • 제9권1호
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    • pp.27-36
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    • 2014
  • This paper presents an adaptive wide-area damping controller (WADC) based on generalized predictive control (GPC) and model identification for damping the inter-area low frequency oscillations in large-scale inter-connected power system. A recursive least-squares algorithm (RLSA) with a varying forgetting factor is applied to identify online the reduced-order linearlized model which contains dominant inter-area low frequency oscillations. Based on this linearlized model, the generalized predictive control scheme considering control output constraints is employed to obtain the optimal control signal in each sampling interval. Case studies are undertaken on a two-area four-machine power system and the New England 10-machine 39-bus power system, respectively. Simulation results show that the proposed adaptive WADC not only can damp the inter-area oscillations effectively under a wide range of operation conditions and different disturbances, but also has better robustness against to the time delay existing in the remote signals. The comparison studies with the conventional lead-lag WADC are also provided.

Wage Determinants Analysis by Quantile Regression Tree

  • Chang, Young-Jae
    • Communications for Statistical Applications and Methods
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    • 제19권2호
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    • pp.293-301
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    • 2012
  • Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.