• 소음진동
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• 제7권4호
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• pp.605-612
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• 1997

A state feedback controller and an observer have been developed and analyzed for an aircraft's safe landing in the windshear called microburst. The observer estimates the ambient wind field as well as the full-order longitudinal state vector. The controller uses the wind and state estimates for guiding the control inputs for safe landing. For the observer and controller gains, the design methodologies of linear quadratic estimation and linear quadratic regulation have been exploited. Analysis shows that some of the microburst-induced aircraft accidents in the past might have been avoided with the designed autopilot.

• Korean Journal of Mathematics
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• 제25권1호
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• pp.45-60
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• 2017

This paper focuses on estimation of an non-integral quadratic function (NIQF) and integral quadratic function (IQF) of a random signal in dynamic system described by a linear stochastic differential equation. The quadratic form of an unobservable signal indicates useful information of a signal for control. The optimal (in mean square sense) and suboptimal estimates of NIQF and IQF represent a function of the Kalman estimate and its error covariance. The proposed estimation algorithms have a closed-form estimation procedure. The obtained estimates are studied in detail, including derivation of the exact formulas and differential equations for mean square errors. The results we demonstrate on practical example of a power of signal, and comparison analysis between optimal and suboptimal estimators is presented.

• 대한기계학회논문집
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• 제18권9호
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• pp.2312-2321
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• 1994

In this work the dynamics of an electromagnetic levitation system is described by a set of three first order nonlinear ordinary differential equations. The objective is to design a digital linear controller which takes the inherent instability of the uncontrolled system and the disturbing force into consideration. The controller is made by employing digital linear quadratic(LQ) design methodology and the unknown state variables are estimated by the kalman filter. The state estimation is performed using not only an air gap sensor but also both an air gap sensor and a piezoelectric accelerometer. The design scheme resulted in a digital linear controller having good stability and performance robustness in spite of various modelling errors. In case of using both a gap sensor and an accelerometer for the state estimation, the control input was rather stable than that in a system with gap sensor only and the controller dealt with the disturbing force more effectively.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2004년도 추계학술대회
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• pp.53-59
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• 2004

Support vector machine(SVM) approach to regression can be found in information science literature. SVM implements the regularization technique which has been introduced as a way of controlling the smoothness properties of regression function. In this paper, we propose a new estimation method based on quadratic loss SVM for a linear fuzzy regression model of Tanaka's, and furthermore propose a estimation method for nonlinear fuzzy regression. This approach is a very attractive approach to evaluate nonlinear fuzzy model with crisp input and output data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2548-2551
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• 2005

In this paper, a robust receding horizon finite impulse response(FIR) filter is proposed for a class of linear discrete time systems with uncertainty satisfying an integral quadratic constraint. The robust state estimation problem involves constructing the set of all possible states at the current time consistent with given system input, output measurements and the integral quadratic constraint.

• Smart Structures and Systems
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• 제10권1호
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• pp.15-31
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• 2012

This study proposes an active control method to suppress beam-rotating machinery system vibrations. The present control method is a combination of the fuzzy input estimation method (FIEM) and linear quadratic Gaussian problem (LQG) algorithms. The FIEM can estimate the unknown input and optimal states by measuring the dynamic displacement, the optimal estimated states into the feedback control; thereby obtaining the optimal control force for a random linear system. Active vibration control of a beam-rotating machinery system is performed to verify the feasibility and effectiveness of the proposed algorithm. The simulation results demonstrate that the proposed method can suppress vibrations in a beam-machine system more efficiently than the conventional LQG method.

• Journal of the Korean Statistical Society
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• 제10권
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• pp.91-96
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• 1981

The development of Minimum Norm Quadratic Unbiased Estimation (MINQUE) has introduced a unified approach for the estimation of variance components in general linear models. The computational problem has been studied by Liu and Senturia (1977) and Goodnight (1978, setting a-priori values to 0). This paper further simplifies the computation and gives efficient and compact computational algorithm for the MINQUE and dispersion matrix in general linear random model.

• Journal of the Korean Statistical Society
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• 제34권2호
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• pp.141-151
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• 2005

Under the assumption that the three-level factors are quantitative, the linear effects are taken more attention than the quadratic effects of the interaction terms. Webb (1971) presented some small incomplete factorial designs that are mixed two- and three-level designs with 20 or fewer runs. The designs provided the estimating linear-by-linear components of interactions between the three-level factors; moreover, they could also offer estimation of interactions that interest the experiments. Webb used ad hoc methods to find these plans; hence, there was still no unified structure to those experiments. In this paper, we develop the methods to construct the $2^{n}3^3$ and $2^{1}3^3$ designs. The designs constructed by these methods not only supply orthogonal estimates of all the main effects but also permit estimation of all the two-factor interactions not involving the quadratic effects. Furthermore, the designs we find are nearly orthogonal.

• Journal of the Korean Data and Information Science Society
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• 제21권4호
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• pp.813-818
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• 2010

The least squares estimation method for model parameters under failure step-stress accelerated life tests is studied and a numerical example will be given to illustrate the proposed inferential procedures under the compound linear plans proposed as an alternative to the optimal quadratic plan, assuming that the exponential distribution with a quadratic relationship between stress and log-mean lifetime. The proposed compound linear plan for constant stress accelerated life tests and 4:2:1 plan are compared for various situations. Even though the compound linear plan was proposed under constant stress accelerated life tests, we found that this plan did well relatively in failure step-stress accelerated life tests.

• 대한전기학회논문지:전력기술부문A
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• 제48권5호
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• pp.560-570
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• 1999

This paper formulates the suboptimal robust Kalman filtering problem into two coupled Linear Matrix Inequality (LMI) problems by applying Lyapunov theory to the augmented system which is composed of the state equation in the uncertain linear system and the estimation error dynamics. This formulations not only provide the sufficient conditions for the existence of the desired filter, but also construct the suboptimal robust Kalman filter. The proposed filter can guarantee the optimized upper bound of the estimation error variance for uncertain systems with parametric uncertainties in both the state and measurement matrices. In addition, this paper shows how the problem of finding the minimizing solution subject to Quadratic Matrix Inequality (QMI), which cannot be easily transformed into LMI using the usual Schur complement formula, can be successfully modified into a generic LMI problem.