• 제목/요약/키워드: Weighting Matrix

검색결과 196건 처리시간 0.034초

Determination of the Weighting Parameters of the LQR System for Nuclear Reactor Power Control Using the Stochastic Searching Methods

  • Lee, Yoon-Joon;Cho, Kyung-Ho
    • Nuclear Engineering and Technology
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    • 제29권1호
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    • pp.68-77
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    • 1997
  • The reactor power control system is described in the fashion of the order increased LQR system. To obtain the optimal state feedback gain vectors, the weighting matrix of the performance function should be determined. Since the contentional method has some limitations, stochastic searching methods are investigated to optimize the LQR weighting matrix using the modified genetic algorithm combined with the simulated annealing, a new optimizing tool named the hybrid MGA-SA is developed to determine the weighting parameters of the LQR system. This optimizing tool provides a more systematic approach in designing the LQR system. Since it can be easily incorporated with any forms of the cost function, it also provides the great flexibility in the optimization problems.

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Neural Network Image Reconstruction for Magnetic Particle Imaging

  • Chae, Byung Gyu
    • ETRI Journal
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    • 제39권6호
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    • pp.841-850
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    • 2017
  • We investigate neural network image reconstruction for magnetic particle imaging. The network performance strongly depends on the convolution effects of the spectrum input data. The larger convolution effect appearing at a relatively smaller nanoparticle size obstructs the network training. The trained single-layer network reveals the weighting matrix consisting of a basis vector in the form of Chebyshev polynomials of the second kind. The weighting matrix corresponds to an inverse system matrix, where an incoherency of basis vectors due to low convolution effects, as well as a nonlinear activation function, plays a key role in retrieving the matrix elements. Test images are well reconstructed through trained networks having an inverse kernel matrix. We also confirm that a multi-layer network with one hidden layer improves the performance. Based on the results, a neural network architecture overcoming the low incoherence of the inverse kernel through the classification property is expected to become a better tool for image reconstruction.

Partly Random Multiple Weighting Matrices Selection for Orthogonal Random Beamforming

  • Tan, Li;Li, Zhongcai;Xu, Chao;Wang, Desheng
    • Journal of Communications and Networks
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    • 제18권6호
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    • pp.892-901
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    • 2016
  • In the multi-user multiple-input multiple-output (MIMO) system, orthogonal random beamforming (ORBF) scheme is proposed to serve multiple users simultaneously in order to achieve the multi-user diversity gain. The opportunistic space-division multiple access system (OSDMA-S) scheme performs multiple weighting matrices during the training phase and chooses the best weighting matrix to be used to broadcast data during the transmitting phase. The OSDMA-S scheme works better than the original ORBF by decreasing the inter-user interference during the transmitting phase. To save more time in the training phase, a partly random multiple weighting matrices selection scheme is proposed in this paper. In our proposed scheme, the Base Station does not need to use several unitary matrices to broadcast pilot symbol. Actually, only one broadcasting operation is needed. Each subscriber generates several virtual equivalent channels with a set of pre-saved unitary matrices and the channel status information gained from the broadcasting operation. The signal-to-interference and noise ratio (SINR) of each beam in each virtual equivalent channel is calculated and fed back to the base station for the weighting matrix selection and multi-user scheduling. According to the theoretical analysis, the proposed scheme relatively expands the transmitting phase and reduces the interactive complexity between the Base Station and subscribers. The asymptotic analysis and the simulation results show that the proposed scheme improves the throughput performance of the multi-user MIMO system.

CONVERGENCE OF MULTISPLITTING METHODS WITH DIFFERENT WEIGHTING SCHEMES

  • Oh, Se-Young;Yun, Jae-Heon;Han, Yu-Du
    • Journal of applied mathematics & informatics
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    • 제30권3_4호
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    • pp.593-602
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    • 2012
  • In this paper, we first introduce a special type of multisplitting method with different weighting scheme, and then we provide convergence results of multisplitting methods with different weighting schemes corresponding to both the AOR-like multisplitting and the SSOR-like multisplitting.

공간시계열 모형의 칼만필터 추정과 예측 (Kalman-Filter Estimation and Prediction for a Spatial Time Series Model)

  • 이성덕;한은희;김덕기
    • Communications for Statistical Applications and Methods
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    • 제18권1호
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    • pp.79-87
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    • 2011
  • 공간적, 시간적으로 퍼져나가는 전염성이 강한 질병인 수두자료를 이용하여 공간 시계열 자료를 분석하는데 있어 일반적으로 알려진 ARIMA 모형에 적합하여 분석을 행하면 공간적인 정보를 반영하지 못하기 때문에 기존에 시간만을 고려한 시계열 분석방법에 공간통계의 공간적 정보를 반영한 공간시계열 모형을 고려한다. 공간시계열 모형에서 공간의 위치 및 영향은 시계열 모형에 공간적 정보로써 가중치행렬을 더 함으로써 처리 가능해진다. 가중치행렬은 지리적으로 인접한 지역일수록 공간의존도가 높다는 것을 반영한 것이며 공간시계열 모형의 연구에서 가중치행렬은 인접한 지역들은 동일한 영향을 줄 것이라 가정하였다. 따라서 본 논문에서는 공간시계열 모형인 STARMA 모형과 STBL 모형에 대한 식별방법, 통계적 추론 및 예측력 비교에 대해 연구하였고 특히, 모수추정의 알고리즘 비교와 공간시계열 모형의 예측력 비교를 통해 Kalman-Filter 방법의 우수성을 보이고자 한다.

비최소 위상 플랜트에서 LQ-servo 방법 (LQ-servo method for non-minimum phase plants)

  • 서병설;장태우
    • 전자공학회논문지B
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    • 제33B권3호
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    • pp.9-16
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    • 1996
  • LQ-servo is a robustness guaranteed multivariable controller design method based on the LQR structure to improve command following with output feedback. in this paper we introduce a weighting factor on the low frequency part of the state weighting matrix in the performance index in order to increase the low frequency gain of loop transfer function matrix T(s) in the loop shaping design method.

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Receding horizon controller deign for fuzzy systems with input constraints

  • Jeong, Seung-Cheol;Choi, Doo-Jin;Park, Poo-Gyeon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.83.4-83
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    • 2002
  • $\bullet$ We present a state-feedback RHC for discrete-time TS fuzzy systems with input constriants. $\bullet$ The controller employ the current and one-step past information on the fuzzy weighting functions. $\bullet$ It is obtained from the finite horizon optimization problem with the invariant ellipsoid constraint $\bullet$ Under parameterized LMI conditions on the terminal weighting matrix $\bullet$ The closed-loop system stability is guaranteed. $\bullet$ The parameterized linear matrix inequalities are relaxed to a finite number of solvable LMIs.

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On the improvement of the guaranteed stability margins for the discrete time LQ regulator

  • Kwon, Wook-Hyun;Kim, Sang-Woo;Choi, Han-Hong
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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    • pp.913-917
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    • 1989
  • In this paper, the selection method of weighting matrices in the discrete-time LQ problem are suggested in order to improve the guaranteed stability margins, i.e. the gain and phase margins. The asymptotic properties of the solution of the algebraic Riccati equations are investigated by using the closed form solution of the difference Riccati equations. It is shown that the solution of the algebraic Riccati equations monotonically increases as the state weighting matrix Q or the control weighting matrix R increase. The increasing rate of the solution is shown to be much less than that of R for large R. It is also proven that the guaranteed stability margins increases as the ratio between Q and R decreases.

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LQ-servo를 이용한 강인한 PI제어기 설계 (Robust PI controller design using LQ-servo)

  • 이동영;윤성오;서병설
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.577-580
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    • 1996
  • LQ-servo is a stability-robustness guaranteed multivariable controller design method based on the LQR structure to improve command following performance with output feedback. In this paper, a new type of PI controller based on LQ-servo is introduced. Then, Command following performance is improved using the limiting behavior of the control gain and weighting factors on the low frequency part of design parameter Q that is the state weighting matrix in the cost function.

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쌍안정 TN LCD의 고속 매트릭스 어드레싱을 위한 패널 파라미터와 구동 파형의 최적화 (Optimization of panel parameters and drive signals for high-speed matrix addressing of a bistable twisted-nematic LCD)

  • 이기동;박구현;장기철;윤태훈;김재창;이응상
    • 한국광학회지
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    • 제9권6호
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    • pp.417-422
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    • 1998
  • 쌍안정 TN LCD를 매트릭스 어드레싱 구동을 할 때 패널 파라미터와 구동 파형을 최적화하는 방법을 제시하였다. 쌍안정 TN 액정 셀에서 데이터 전압이 광 수위칭 특성에 미치는 영향을 측정하였고 이를 이론적으로 모델링 하였다. 스위칭에 데이터 전압이 미치는 영향을 고려하기 위해 시간의 함수로써 weighting 함수를 도입하였다. Weighting 함수를 알아내면 최소의 데이터 펄스폭을 계산함으로써 멀티플렉싱 구동을 위한 최대의 구동 라인 수를 계산할 수 있다. 또한 패널 파라미터(예, d/p)를 변화 시키면서 테스트 셀을 구동하면 고속 동작을 위한 파라미터를 최적화할 수 있다. 이로부터 이론적 예측과 실험 결과가 잘 일치하는 것을 확인하였다.

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