• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.56.5-56
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• 2002

This paper studies on the feedback linearization of the looper system for hot strip mills, where the looper system plays an important role in regulating the strip tension. Firstly, nonlinear dynamic equations of the looper system are simply introduced. Secondly, using the static feedback linearization algorithm, a linear model of the looper system is obtained, of which usefulness is validated from comparison between the linear model and the nonlinear model, and design of LQI(Linear Ouadratic Integral optimal control) and ILQ (Inverse Linear Quadratic optimal control) looper control systems. In result, it is shown that the linear looper model by the feedback linearization well describes nonlin...

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.268-271
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• 2008

In this paper, we introduce the notions of a fuzzy convergence of sequences, fuzzy Cauchy sequence and the related fuzzy completeness on a fuzzy normed linear space. And we investigate some properties relative to fuzzy normed linear spaces. In particular, we prove an equivalent conditions that a fuzzy norm defined on a ordinary normed linear space is fuzzy complete.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.65-73
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• 1997

The effects of time-sampling on linear output regulation problem is ivestigated. It is found that the solvability of linear output regulation problem is generally not robust with respect to time-sampling although the solvability of that for single inut and single output linear systems and the solvability of linear robust output regulation problem are preserved under time-sampling. The resutls imply that one needs to seek a better approximate sampled-data output regulator.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.758-767
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• 2000

The properties of linear time-varying(LTV) systems vary because of the time-varying property of plant parameters. The generalized controller design method for linear time-varying systems does not exit because the analytic soultion of dynamic equation has not been found yet. Hence, to design a controller for LTV systems, the robust control methods for uncertain LTI systems which are the approximation of LTV systems have been generally ised omstead. However, these methods are not sufficient to reflect the fast dynamics of the original time-varying systems such as missiles and supersonic aircraft. In general, both the performance and the robustness of the control system which is designed with these are not satisfactory. In addition, since a better model will give the more robustness to the controlled system, a gain scheduling technique based on LTI controller design methods has been uesd to solve time problem. Therefore, we propose a new gain scheduled QFT method for LTV systems based on neural networks in this paper. The gain scheduled QFT involves gain dcheduling procedured which are the first trial for QFT and are well suited consideration of the properties of the existing QFT method. The proposed method is illustrated by a numerical example.

• ETRI Journal
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• v.29 no.3
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• pp.322-328
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• 2007

We propose a direct-sequence pulse-amplitude modulation (DS-PAM) ultra-wideband (UWB) system which employs a non-linear chirp waveform instead of the conventional Gaussian monocycle in this paper. In the approved frequency for UWB, there exist myriad narrowband interferers. Specifically, we focus on the mutual interference between UWB systems and 802.11a WLAN. This paper offers a method to suppress this in-band narrowband interference by introducing a kind of non-linear chirp waveform. Using the proposed non-linear chirp waveform, the effects of one or more narrowband interference sources with different frequencies can be suppressed. System performance of UWB systems in the narrowband interference environment can be improved. Computer simulations with additive white Gaussian noise successfully demonstrate an increase in performance with the proposed system as compared to traditional linear chirp systems.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.40-44
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• 2007

Light rail vehicle is optimized vehicle system for complex urban circumstance. LRT systems have many merits such as improve accuracy, speediness and safety. There are many LRT systems such as monorail, tram, automated guideway transit, linear induction motor propulsion and so on. These systems have operated in Japan and other advanced countries. In Korea, local government has many projects to apply the advanced LRT system. But there are no standardized specification, performance test specification, construction specification for monorail system, linear induction motor propulsion system, tram in Korea up to now. So, we need to establish of standardized to economical construction and safety. The linear induction motor system has been usually applied in Japan subway and ART(Advanced Rapid Transit) of Canada. In Korea, the linear induction motor system has been adopted for Yongin LRT and currently under construction. This paper covers the contents and technical base for main items of rolling stock, performance standard, carbody structure, bogie, electronic unit and brake equipment in order to implement linear induction motor LRT system according to local conditions.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.2
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• pp.29-36
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• 2004

This paper deals with a fractional model reduction for linear systems with time varying delayed states. A contractive coprime factorization of linear time delayed systems is defined and obtained by solving linear matrix inequalities. Using generalize controllability and observability gramians of tile contractive coprime factor, a balanced state space realization of the system is derived. The reduced model will be obtained by truncating states in the balanced realization and an upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is illustrated.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.420-424
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• 1993

New conditions for the exponential stability for both linear nonautnomous finite and a class of infinite dimensional systems described by parabolic partial differential equations (PDE's) are derived. The results for the parabolic systems are derived via semigroup approach.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.202-205
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• 1988

Several sufficient condition which guarantee the stability of linear state delay systems are derived. And the delay margin which guarantees the stability of the delay systems are presented.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.