• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.3
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• pp.279-282
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• 2014

In this paper, we report a new sharp inequality of interpolation type in $\mathbb{R}^n$. This inequality is for controlling weighted average of a function via $L^n$ norm of the gradient of a function together with its' certain exponential norm.

• Bulletin of the Korean Mathematical Society
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• v.50 no.3
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• pp.901-914
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• 2013

Kwon and Bae gave an interpolation for a continuous form of H$\ddot{o}$lder's inequality for a real-valued bounded measurable function on a product of measure spaces. It is given some generalizations of their result.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.48.3-48
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• 2001

A gain-scheduled autopilot design for a bank-to-turn (BTT) missile is developed by using the Linear Matrix Inequality (LMI) optimization technique and a state-space lineal interpolation method. The missile dynamics are brought to a quasilinear parameter varying (quasi-LPV) form. Robust linear control design method is used to obtain state feedback controllers for the LPV systems with exogenous disturbances at the frozen values of the scheduling parameters. Two gam-scheduled controllers for the pitch axis and the yaw/roll axis are constructed by linearly interpolating the robust state-feedback gains. The designed controller is applied to a nonlinear six-degree-of-freedom (6-DOF) simulations.

• Journal of Power System Engineering
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• v.4 no.3
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• pp.72-80
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• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identification. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identification are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identity the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.

• Bulletin of the Korean Mathematical Society
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• v.55 no.1
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• pp.267-296
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• 2018

This paper studies the Cauchy problem and blow-up phenomena for a new generalized Camassa-Holm equation with cubic nonlinearity in the nonhomogeneous Besov spaces. First, by means of the Littlewood-Paley decomposition theory, we investigate the local well-posedness of the equation in $B^s_{p,r}$ with s > $max\{{\frac{1}{p}},\;{\frac{1}{2}},\;1-{\frac{1}{p}}\},\;p,\;r{\in}[0,{\infty}]$. Second, we prove that the equation is locally well-posed in $B^s_{2,r}$ with the critical index $s={\frac{1}{2}}$ by virtue of the logarithmic interpolation inequality and the Osgood's Lemma, and it is shown that the data-to-solution mapping is $H{\ddot{o}}lder$ continuous. Finally, we derive two kinds of blow-up criteria for the strong solution by using induction and the conservative property of m along the characteristics.