• 제목/요약/키워드: Least squares solution

검색결과 204건 처리시간 0.024초

회귀 최소 자승법을 이용한 고조파 발생원 추정 연구 (Estimation of Harmonic Sources in a Power System using Recursive Least-Squares Technique)

  • 한종훈;이계병;박창현;장길수
    • 전기학회논문지
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    • 제60권9호
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    • pp.1639-1645
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    • 2011
  • A technique to allocate responsibilities among the interested parties in electric power system with harmonic voltage distortion at the point of common coupling (PCC) has been presented. The recursive least-squares technique has been used to estimate the parameters of the Thevenin equivalent load model. The validity of the technique has been verified using a simulation which considered the voltage waveform distortion at the PCC between the utility and two industrial consumers. With the estimated data from the measured voltage and current waveform at the PCC, the individual contributions to the distortion of voltage waveform at an interested harmonic frequency have been calculated and could provide a flexible solution to identify the source of harmonic pollution in distribution systems.

비용함수와 서브 골을 이용한 비선형 최적화 방법 기반의 이동로봇 장애물 회피 주행 (Mobile Robot Navigation with Obstacle Avoidance based on the Nonlinear Least Squares Optimization Method using the Cost Function and the Sub-Goal Switching)

  • 정영종;김곤우
    • 전기학회논문지
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    • 제63권9호
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    • pp.1266-1272
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    • 2014
  • We define the mobile robot navigation problem as an optimization problem to minimize the cost function with the pose error between the goal position and the position of a mobile robot. Using Gauss-Newton method for the optimization, the optimal speeds of the left and right wheels can be found as the solution of the optimization problem. Especially, the rotational speed of wheels of a mobile robot can be directly related to the overall speed of a mobile robot using the Jacobian derived from the kinematic model. When the robot detects the obstacle using sensors, the sub-goal switching method is adopted for the efficient obstacle avoidance during the navigation. The performance was evaluated using the simulation and the simulation results show the validity of the proposed method.

Alternating-Projection-Based Channel Estimation for Multicell Massive MIMO Systems

  • Chen, Yi Liang;Ran, Rong;Oh, Hayoung
    • Journal of information and communication convergence engineering
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    • 제16권1호
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    • pp.17-22
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    • 2018
  • In massive multiple-input multiple-output (MIMO) systems, linear channel estimation algorithms are widely applied owing to their simple structures. However, they may cause pilot contamination, which affects the subsequent data detection performance. Therefore, herein, for an uplink multicell massive multiuser MIMO system, we consider using an alternating projection (AP) for channel estimation to eliminate the effect of pilot contamination and improve the performance of data detection in terms of the bit error rates as well. Even though the AP is nonlinear, it iteratively searches the best solution in only one dimension, and the computational complexity is thus modest. We have analyzed the mean square error with respect to the signal-to-interference ratios for both the cooperative and non-cooperative multicell scenarios. From the simulation results, we observed that the channel estimation results via the AP benefit the following signal detection more than that via the least squares for both the cooperative and non-cooperative multicell scenarios.

Combining Empirical Feature Map and Conjugate Least Squares Support Vector Machine for Real Time Image Recognition : Research with Jade Solution Company

  • Kim, Byung Joo
    • International Journal of Internet, Broadcasting and Communication
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    • 제9권1호
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    • pp.9-17
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    • 2017
  • This paper describes a process of developing commercial real time image recognition system with company. In this paper we will make a system that is combining an empirical kernel map method and conjugate least squares support vector machine in order to represent images in a low-dimensional subspace for real time image recognition. In the traditional approach calculating these eigenspace models, known as traditional PCA method, model must capture all the images needed to build the internal representation. Updating of the existing eigenspace is only possible when all the images must be kept in order to update the eigenspace, requiring a lot of storage capability. Proposed method allows discarding the acquired images immediately after the update. By experimental results we can show that empirical kernel map has similar accuracy compare to traditional batch way eigenspace method and more efficient in memory requirement than traditional one. This experimental result shows that proposed model is suitable for commercial real time image recognition system.

Nonlinear Optimal Control of an Input-Constrained and Enclosed Thermal Processing System

  • Gwak, Kwan-Woong;Masada, Glenn Y.
    • International Journal of Control, Automation, and Systems
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    • 제6권2호
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    • pp.160-170
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    • 2008
  • Temperature control of an enclosed thermal system which has many applications including Rapid Thermal Processing (RTP) of semiconductor wafers showed an input-constraint violation for nonlinear controllers due to inherent strong coupling between the elements [1]. In this paper, a constrained nonlinear optimal control design is developed, which accommodates input constraints using the linear algebraic equivalence of the nonlinear controllers, for the temperature control of an enclosed thermal process. First, it will be shown that design of nonlinear controllers is equivalent to solving a set of linear algebraic equations-the linear algebraic equivalence of nonlinear controllers (LAENC). Then an input-constrained nonlinear optimal controller is designed based on that LAENC using the constrained linear least squares method. Through numerical simulations, it is demonstrated that the proposed controller achieves the equivalent performances to the classical nonlinear controllers with less total energy consumption. Moreover, it generates the practical control solution, in other words, control solutions do not violate the input-constraints.

Meshless equilibrium on line method (MELM) for linear elasticity

  • Sadeghirad, A.;Mohammadi, S.;Kani, I. Mahmoudzadeh
    • Structural Engineering and Mechanics
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    • 제35권4호
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    • pp.511-533
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    • 2010
  • As a truly meshfree method, meshless equilibrium on line method (MELM), for 2D elasticity problems is presented. In MELM, the problem domain is represented by a set of distributed nodes, and equilibrium is satisfied on lines for any node within this domain. In contrary to conventional meshfree methods, test domains are lines in this method, and all integrals can be easily evaluated over straight lines along x and y directions. Proposed weak formulation has the same concept as the equilibrium on line method which was previously used by the authors for enforcement of the Neumann boundary conditions in the strong-form meshless methods. In this paper, the idea of the equilibrium on line method is developed to use as the weak forms of the governing equations at inner nodes of the problem domain. The moving least squares (MLS) approximation is used to interpolate solution variables in this paper. Numerical studies have shown that this method is simple to implement, while leading to accurate results.

Least squares decoding in binomial frequency division multiplexing

  • Myungsup Kim;Jiwon Jung;Ki-Man Kim
    • ETRI Journal
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    • 제45권2호
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    • pp.277-290
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    • 2023
  • This paper proposes a method that can reduce the complexity of a system matrix by analyzing the characteristics of a pseudoinverse matrix to receive a binomial frequency division multiplexing (BFDM) signal and decode it using the least squares (LS) method. The system matrix of BFDM can be expressed as a band matrix, and as this matrix contains many zeros, its amount of calculation when generating a transmission signal is quite small. The LS solution can be obtained by multiplying the received signal by the pseudoinverse matrix of the system matrix. The singular value decomposition of the system matrix indicates that the pseudoinverse matrix is a band matrix. The signal-to-interference ratio is obtained from their eigenvalues. Meanwhile, entries that do not contribute to signal generation are erased to enhance calculation efficiency. We decode the received signal using the pseudoinverse matrix and the removed pseudoinverse matrix to obtain the bit error rate performance and to analyze the difference.

해석적 자료를 이용한 최소자승 추정법의 성능 개선 - 원자로보호계통에의 응용 - (Improvement of Accuracy for Least Square Estimator Combining Analytic Solution - Application to Reactor Protection System)

  • 최유선;박문규;차균호;이창섭
    • 한국에너지공학회:학술대회논문집
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    • 한국에너지공학회 2000년도 추계 학술발표회 논문집
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    • pp.111-114
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    • 2000
  • 본 논문은 선형모델의 모델 계수의 결정방법으로 사용되는 최소자승법 (Least Squares Method, LSM)의 단점을 해결하기 위해 해석적으로 계산된 자료를 함께 적용하는 방법과 원자로의 출력분포 측정을 위한 SAM (Shape Annealing Matrix) 결정에 적용한 결과를 기술하고 있다. 해석적 자료를 함께 적용할 경우 연료 연소에 따른 원자로 특성변화를 적절히 반영하여 LSM 추정치의 정확도를 크게 개선할 수 있음을 확인하였다.

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통계적 오차보상 기법을 이용한 센서 네트워크에서의 RDOA 측정치 기반의 표적측위 (Stochastic Error Compensation Method for RDOA Based Target Localization in Sensor Network)

  • 최가형;나원상;박진배;윤태성
    • 전기학회논문지
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    • 제59권10호
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    • pp.1874-1881
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    • 2010
  • A recursive linear stochastic error compensation algorithm is newly proposed for target localization in sensor network which provides range difference of arrival(RDOA) measurements. Target localization with RDOA is a well-known nonlinear estimation problem. Since it can not solve with a closed-form solution, the numerical methods sensitive to initial guess are often used before. As an alternative solution, a pseudo-linear estimation scheme has been used but the auto-correlation of measurement noise still causes unacceptable estimation errors under low SNR conditions. To overcome these problems, a stochastic error compensation method is applied for the target localization problem under the assumption that a priori stochastic information of RDOA measurement noise is available. Apart from the existing methods, the proposed linear target localization scheme can recursively compute the target position estimate which converges to true position in probability. In addition, it is remarked that the suggested algorithm has a structural reconciliation with the existing one such as linear correction least squares(LCLS) estimator. Through the computer simulations, it is demonstrated that the proposed method shows better performance than the LCLS method and guarantees fast and reliable convergence characteristic compared to the nonlinear method.

Sensors Comparison for Observation of floating structure's movement

  • Trieu, Hang Thi;Han, Dong Yeob
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2014년도 추계학술대회
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    • pp.219-221
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    • 2014
  • The objective of this paper is to simulate the dynamic behavior of a floating structure model, using image processing and close-range photogrammetry, instead of the contact sensors. Previously, the movement of structure was presented through the exterior orientation estimation of a single camera by space resection. The inverse resection yields the 6 orientation parameters of the floating structure, with respect to the camera coordinate system. The single camera solution is of interest in applications characterized by restriction in term of costs, unfavorable observation conditions, or synchronization demands when using multiple cameras. This article discusses the theoretical determinations of camera exterior orientation based on Direct Linear Transformation and photogrammetric resection using least squares adjustment. The proposed method was used to monitor the motion of a floating model. The results of six degrees of freedom (6-DOF) by inverse resection show that the appropriate initial values by DLT can be effectually applied in least squares adjustment, to obtain the precision of exterior orientation parameters. Additionally, a comparison between the close-range photogrammetry and total station results was feasibly verified. Therefore, the proposed method can be considered as an efficient solution to simulating the movement of floating structure.

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