• 제목/요약/키워드: constrained

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Cook-Type Influence Measure in Constrained Regression Models

  • Kim, Myung-Geun
    • Communications for Statistical Applications and Methods
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    • 제15권2호
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    • pp.229-234
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    • 2008
  • A Cook-type distance is considered for investigating the influence of observations in constrained regression models. Its exact sampling distribution is derived, which is used for judging whether each observation is influential or not. A numerical example is provided for illustration.

일반화된 제한 최소자승법을 이용한 능동 소음제어에 관한 연구 (A study on the active noise control using generalized CLMS)

  • 나희승;박영진
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.52-57
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    • 1993
  • Conventional active control algorithm for duct system is developed without considering problems of constrained structure. Therefore it destroys the constrained structures of the weights or parameters. A new LMS algorithm, which does keep the constraints, is proposed for systems with known constrained structure. It is based on error-back propagation. The stability analysis and simulation example are also included.

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Constrained $H_\infty$ Optimal Control

  • Park, Jinhoon
    • 전기의세계
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    • 제49권9호
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    • pp.4-8
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    • 2000
  • Recently we have shown based on Lyapunov theorem that the closed loop system with the constrained infinite horizon H$\infty$ optimal controller is exponentially stable. moreover the on-line feedback implementation of the constrained infinite horizon H$\infty$ optimal control based on quadratic programs has been proposed. n this paper we summarize and discuss these results.

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Application of Constrained Bayes Estimation under Balanced Loss Function in Insurance Pricing

  • Kim, Myung Joon;Kim, Yeong-Hwa
    • Communications for Statistical Applications and Methods
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    • 제21권3호
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    • pp.235-243
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    • 2014
  • Constrained Bayesian estimates overcome the over shrinkness toward the mean which usual Bayes and empirical Bayes estimates produce by matching first and second empirical moments; subsequently, a constrained Bayes estimate is recommended to use in case the research objective is to produce a histogram of the estimates considering the location and dispersion. The well-known squared error loss function exclusively emphasizes the precision of estimation and may lead to biased estimators. Thus, the balanced loss function is suggested to reflect both goodness of fit and precision of estimation. In insurance pricing, the accurate location estimates of risk and also dispersion estimates of each risk group should be considered under proper loss function. In this paper, by applying these two ideas, the benefit of the constrained Bayes estimates and balanced loss function will be discussed; in addition, application effectiveness will be proved through an analysis of real insurance accident data.

Optimal actuator selection for output variance constrained control

  • 김재훈
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.565-569
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    • 1993
  • In this paper, a specified number of actuators are selected from a given set of admissible actuators. The selected set of actuators is likely to use minimum control energy while required output variance constraints are guaranteed to be satisfied. The actuator selection procedure is an iterative algorithm composed of two parts; an output variance constrained control and an input variance constrained control algorithm. The idea behind this algorithm is that the solution to the first control problem provides the necessary weighting matrix in the objective function of the second optimization problem, and the sensitivity information from the second problem is utilized to delete one actuator. For variance constrained control problems, by considering a dual version of each control problem an efficient algorithm is provided, whose convergence properties turn out to be better than an existing algorithm. Numerical examples with a simple beam are given for both the input/output variance constrained control problem and the actuator selection problem.

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General Linearly Constrained Broadband Adaptive Arrays in the Eigenvector Space

  • Chang, Byong Kun
    • Journal of information and communication convergence engineering
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    • 제15권2호
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    • pp.73-78
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    • 2017
  • A general linearly constrained broadband adaptive array is examined in the eigenvector space with respect to the optimal weight vector and the adaptive algorithm. The optimal weight vector and the general adaptive algorithm in the eigenvector space are obtained by eigenvector matrix transformation. Their operations are shown to be the same as in the standard coordinate system except for the relevant transformed vectors and matrices. The nulling performance of the general linearly constrained broadband adaptive array depends on the gain factor such that the constraint plane is shifted perpendicularly to the origin by an increase in the gain factor. The general linearly constrained broadband adaptive array is observed to perform better than a conventional linearly constrained adaptive array in a coherent signal environment, while the former performs similarly to the latter in a non-coherent signal environment.

Control of Two-Link Manipulator Via Feedback Linearization and Constrained Model Based Predictive Control

  • Son, Won-Kee;Park, Jin-Young;Ryu, Hee-Seb;Kwon, Oh-Kyu
    • Transactions on Control, Automation and Systems Engineering
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    • 제2권4호
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    • pp.221-227
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    • 2000
  • This paper combines the constrained model predictive control with the feedback linearization to solve a nonlinear system control problem with input constraints. The combined approach consists of two steps: Firstly, the nonlinear model is linearized by the feedback linearization. Secondly, based on the linearized model, the constrained model predictive controller is designed taking input constraints into consideration. The proposed controller is applied to two link robot system, and tracking performances of the controller are investigated via some simulations, where the comparisons are done for the cases of unconstrained, constrained input in feedback linearization.

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