• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.843-847
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• 2011

In this note, a proof of Utkin's theorem is presented for the SI(Single Input) uncertain integral linear case. The invariance theorem with respect to the two transformation methods so called the two diagonalization methods are proved clearly and comparatively for SI uncertain integral linear systems. With respect to the sliding surface transformation, the equation of the sliding mode, the sliding surface is invariant. Both the applied control inputs have the same gains. By means of the two transformation methods the same results can be obtained. Through an illustrative example and simulation study, the usefulness of the main results is verified.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1504-1508
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• 1996

In this paper, we derive dynamic equation of helicopter and design controller based on variable structure system. It is difficult to control helicopter because it has non-linear coupling between input and output of system and is MIMO system. The design of control law is considered here using variable structure methodology giving the robustness to parameter variations and invariance to some subsets of external disturbance. However we derive dynamic equations of helicopter and design stabilizing variable structure controller. Also, simulation results are given in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.955-959
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• 2003

A technique for realizing linear phase IIR filters has been proposed by Powell-Chau which gives a real-time implementation of H(z-1).H(z), where H(z) is a causal nonlinear phase IIR filter. Powell-Chau system is linear but not timeinvariant system. Therefore, that system has group delay response that exhibits a minor sinusoidal variation superimposed on a constant value. In the signal processing, this oscillation seriously degrade the signal quality. Unfortunately, that system has a large sample delay of 4L and also more computational complexity. Proposed system is present a reduced computational complexity technique by moved the numerator polynomial of H(1/z) out to cascade with causal filter H(z) and remain only all-pole of H(1/z), then applied truncated infinite impulse response to finite with truncated IIR filtel $H_L$(z) and L sample delay to subtract the output sequence from the top and bottom filter. Proposed system is linear time invariance and group delay response and total harmonic distortion are also improved.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.6
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• pp.8-14
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• 2011

In this note, a proof of Utkin's theorem is presented for SI(Single input) uncertain linear systems. The invariance theorem with respect to the two transformation methods so called the two diagonalization methods is proved clearly and comparatively for SI uncertain linear systems. With respect to the sliding surface transformation, the equation of the sliding mode i.e., the sliding surface is invariant. The control inputs by the two transformation methods both have the same gains. By means of the two transformation methods, the same results can be obtained. Through an illustrative example and simulation study, the usefulness of the main results is verified.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.891-897
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• 2018

In this paper, we propose a blind estimation scheme for the antenna spacing of nonuniform linear array MIMO radar using distributed electronic sensors based on ESPRIT. We present a blind method to separate orthogonal waveforms of a MIMO radar based on the antenna spacing estimation. The estimated orthogonal waveforms of a MIMO radar can be used for disabling opponent MIMO radars.

• Communications of the Korean Mathematical Society
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• v.9 no.4
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• pp.951-959
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• 1994

A sequence ${X_j : j \geq 1}$ of random variables is said to be pairwise positive quadrant dependent (pairwise PQD) if for any real $r-i,r_j$ and $i \neq j$ $$ P{X_i > r_i,X_j > r_j} \geq P{X_i > r_i}P{X_j > r_j} $$ (see [8]) and a sequence ${X_j : j \geq 1}$ of random variables is said to be associated if for any finite collection ${X_{i(1)},...,X_{j(n)}}$ and any real coordinatewise nondecreasing functions f,g on $R^n$ $$ Cov(f(X_{i(1)},...,X_{j(n)}),g(X_{j(1)},...,X_{j(n)})) \geq 0, $$ whenever the covariance is defined (see [6]). Instead of association Cox and Grimmett's [4] original central limit theorem requires only that positively linear combination of random variables are PQD (cf. Theorem $A^*$).

• Journal of the Korean Society of Industry Convergence
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• v.18 no.3
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• pp.157-166
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• 2015

In this paper, we proposed a new robust control scheme to implement stable control of robot manipulators including nonlinear perameters The proposed robust controller is composed of a nonlinear controller and linear compemsation controller. It shows a good robust performance in reaching mode which does not possess invariance property. Thus, the proposed nonlinear controller showed a good robust performance in the whole region, It was illustrated that the proposed control showed a good transient response and trajectory tracking performance for robot manipulator with four joint by experiments.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.883-902
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• 2012

In this work we deal with a nonlinear dynamical system, namely the wastewater treatment model. We proceed to a dynamical analysis of the model. Invariance, boundness, controllability and the sensitivity with respect the initial conditions are studied. On the other hand, using the nonsmooth analysis tools, we look for the viability of the model, that is, the necessary and sufficient conditions under which trajectories move in a suitable time-moving sets, to avoid the washing problem (died of bacteria).

• ETRI Journal
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• v.32 no.3
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• pp.490-492
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• 2010

This letter proposes a robust feature extraction method using a spatially normalized mean for temporal ordinal measurement. Before computing a rank matrix from the mean values of non-overlapped blocks, each block mean is normalized so that it obeys the invariance property against linear additive and subtractive noise effects and is insensitive against multiplied and divided noise effects. Then, the temporal ordinal measures of spatially normalized mean values are computed for the feature matching. The performance of the proposed method showed about 95% accuracy in both precision and recall rates on various distortion environments, which represents the 2.7% higher performance on average compared to the temporal ordinal measurement.

• East Asian mathematical journal
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• v.5 no.1
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• pp.95-110
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• 1989

In a general variance component model, nonnegative quadratic estimators of the components of variance are considered which are invariant with respect to mean value translaion and have minimum bias (analogously to estimation theory of mean value parameters). Here the minimum is taken over an appropriate cone of positive semidefinite matrices, after having made a reduction by invariance. Among these estimators, which always exist the one of minimum norm is characterized. This characterization is achieved by systems of necessary and sufficient condition, and by a cone restricted pseudoinverse. In models where the decomposing covariance matrices span a commutative quadratic subspace, a representation of the considered estimator is derived that requires merely to solve an ordinary convex quadratic optimization problem. As an example, we present the two way nested classification random model. An unbiased estimator is derived for the mean squared error of any unbiased or biased estimator that is expressible as a linear combination of independent sums of squares. Further, it is shown that, for the classical balanced variance component models, this estimator is the best invariant unbiased estimator, for the variance of the ANOVA estimator and for the mean squared error of the nonnegative minimum biased estimator. As an example, the balanced two way nested classification model with ramdom effects if considered.