• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.141-150
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• 1998

This paper presents a dynamical anti-reset windup (ARW) compensation method for saturating control systems with multiple controllers and/or multiloop configuration. By regarding the difference of controller states in the absence and presence of saturating actuators as an objective function, the dynamical compensator which minimizes the objective function is derived in an integrated fashion. The proposed dynamical compensator is a closed form of plant and controller parameters. The resulting dynamics of compensated controller reflects the linear closed-loop system. The proposed method guarantees total stability of the resulting system. The effectiveness of the proposed method is illustrated by applying it to a servo motor control system. The paper is an extension of the results in Park and Choi[1].

• Journal of the Chungcheong Mathematical Society
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• v.30 no.3
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• pp.341-355
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• 2017

This paper is devoted to some dynamical properties such as transitivity, mixing and specification of two discrete dynamical systems (X, f) and ($2^X$, ${\bar{f}}$) on compact metric spaces.

• Bulletin of the Korean Mathematical Society
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• v.48 no.1
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• pp.35-50
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• 2011

We construct the index pairs of an isolated neighborhood for a dispersive dynamical system and investigate the existence of an index pair which is stable under small perturbations of the dispersive dynamical systems.

• Bulletin of the Korean Mathematical Society
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• v.31 no.2
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• pp.289-295
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• 1994

Let (A,G,.alpha.) be a $C^{*}$-dynamical system. In [3] the classical notions of ergodic properties of topological dynamical systems such as topological transitivity, minimality, and uniquely ergodicity are extended and analyzed in the context of non-abelian $C^{*}$-dynamical systems. We showed in [2] that if G is a compact group, then minimality, topological transitivity, uniquely ergodicity, and weakly ergodicity of the $C^{*}$-dynamical system (A,G,.alpha.) are equivalent.alent.

• Journal of the Chungcheong Mathematical Society
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• v.3 no.1
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• pp.1-11
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• 1990

The purpose of this paper is to study the chain recurrent sets under persistent dynamical systems, and give a necessary condition for a persistent dynamical system to be topologically stable. Moreover, we show that the various recurrent sets depend continuously on persistent dynamical system.

• Journal of the Korean Mathematical Society
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• v.49 no.4
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• pp.703-713
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• 2012

In this paper we study ${\omega}$-limit sets and attraction of non-autonomous discrete dynamical systems. We introduce some basic concepts such as ${\omega}$-limit set and attraction for non-autonomous discrete system. We study fundamental properties of ${\omega}$-limit sets and discuss the relationship between ${\omega}$-limit sets and attraction for non-autonomous discrete dynamical systems.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.74-80
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• 2013

This study describes structural reliability analysis of actively-controlled structure for which random vibration analysis is incorporated into the first-order reliability method (FORM) framework. The existing approaches perform the reliability analysis based on the RMS response, whereas the proposed study uses the peak response for the reliability analysis. Therefore, the proposed approach provides us a meaningful performance measure of the active control system, i.e., realistic failure probability. In addition, it can deal with the uncertainties in the system parameters as well as the excitations in single-loop reliability analysis, whereas the conventional random vibration analysis requires double-loop reliability analysis; one is for the system parameters and the other is for stochastic excitations. The effectiveness of the proposed approach is demonstrated through a numerical example where the proposed approach shows fast and accurate reliability (or inversely failure probability) assessment results of the dynamical active control system against random seismic excitations in the presence of parametric uncertainties of the dynamical structural system.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.563-573
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• 2018

An Expert Seasonal Prediction System for operational Seasonal Outlook (ESPreSSO) is developed based on the APEC Climate Center (APCC) Multi-Model Ensemble (MME) dynamical prediction and expert-guided statistical downscaling techniques. Dynamical models have improved to provide meaningful seasonal prediction, and their prediction skills are further improved by various ensemble and downscaling techniques. However, experienced scientists and forecasters make subjective correction for the operational seasonal outlook due to limited prediction skills and biases of dynamical models. Here, a hybrid seasonal prediction system that grafts experts' knowledge and understanding onto dynamical MME prediction is developed to guide operational seasonal outlook in Korea. The basis dynamical prediction is based on the APCC MME, which are statistically mapped onto the station-based observations by experienced experts. Their subjective selection undergoes objective screening and quality control to generate final seasonal outlook products after physical ensemble averaging. The prediction system is constructed based on 23-year training period of 1983-2005, and its performance and stability are assessed for the independent 11-year prediction period of 2006-2016. The results show that the ESPreSSO has reliable and stable prediction skill suitable for operational use.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.3
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• pp.487-492
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• 2002

In this paper, we proposed a control method of an unknown nonlinear system using a dynamical neural network. The proposed method is composed of neural network of state space model type, performs for a unknown nonlinear system, identification with using the dynamical neural network, and then a nonlinear adaptive controller is designed with these identified informations. In order to verify the effectiveness of the proposed method, we simulated one-link manipulator. The simulation results showed the effectiveness of using the dynamical neural network in the adaptive control of one-link manipulator.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.595-604
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• 2012

In this article, we consider chaotic behavior happened in nonsmooth dynamical systems. To quantify such a behavior, a computation of Lyapunov exponents for chaotic orbits of a given nonsmooth dynamical system is focused. The Lyapunov exponent is a very important concept in chaotic theory, because this quantity measures the sensitive dependence on initial conditions in dynamical systems. Therefore, Lyapunov exponents can decide whether an orbit is chaos or not. To measure the sensitive dependence on initial conditions for nonsmooth dynamical systems, the calculation of Lyapunov exponent plays a key role, but in a theoretical point of view or based on the definition of Lyapunov exponents, Lyapunov exponents of nonsmooth orbit could not be calculated easily, because the Jacobian derivative at some point in the orbit may not exists. We use an algorithmic calculation method for computing Lyapunov exponents using time series for a two dimensional piecewise smooth dynamic system.