• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.506-511
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• 2011

In this paper we investigate some situations in connection with two exact sequences of fuzzy linear maps. Also we obtain a generalization of the work [Theorem4] of Pan [5], and we study the analogies of The Four Lemma and The Five Lemma of homological algebra. Finally we obtain a special exact sequence.

• 전기의세계
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• v.30 no.11
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• pp.728-733
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• 1981

Most of real world systems are highly non-linear. But due to difficulties in analyzing and dealing with it, only the linear system theory is well estabilished. Bilinear system where state and control are linear but not linear jointly is introduced. Here shows that optimal state estimation of stochastic bilinear system requirs infinite dimensional filter, thus onesub-optimal estimator for this system is suggested.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.622-626
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• 2012

This paper presents synchronization of LTV (Linear Time-Varying) MAS (Multi-Agent Systems) with heterogeneous time-varying disturbances under a fixed, connected, and undirected communication network. All the agents can collect only relative state information from their neighborhoods. To achieve synchronization of the MAS, an integral control scheme is proposed based on relative state information between agents.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1993-1998
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• 2004

This paper proposes a new framework for control system design, called the data-based control approach or data space approach, in which the input and output data of a dynamical system is directly and solely used to analyze or design a control system without the employment of any mathematical models like transfer functions, state space equations, and kernel representations. Since, in this approach, most of the analysis and design processes are carried out in the domain of the data space, we introduce some notions of geometrical objects, e.g., the openloop and closed-loop data spaces, which serve as the system representations in the data space. In addition, we establish a relationship between the open-loop and closed-loop data spaces that the closed-loop data space is contained in the open-loop data space as one of its subspaces. By using this relationship, we can derive the data-based stabilization condition for a linear time-invariant discrete-time system, which leads to a linear matrix inequality with a rank constraint.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1604-1607
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• 2004

In this paper, we consider a problem of asymptotic output regulation of a class of uncertain nonlinear systems by output feedback. The system under consideration is in the Parametric-Pure-Feedback Form, which does not satisfy the existing conditions such as the triangularity condition or the Lipschitz condition. We propose a linear output feedback controller with a scaling factor, which asymptotically regulates the output of the considered system.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.1
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• pp.1-4
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• 1996

This paper presents a state feedback $H^{\infty}$ controller design method for linear systems with delayed states and inputs. We derive a sufficient condition that the closed-loop system is asymptotically stable for all time-delays and that the $H^{\infty}$-norm of the closed-loop transfer function is less than or equal to some prescribed level $\gamma$. And we propose a sufficient condition for the existence of a state feedback $H^{\infty}$ controller using a form of linear matrix inequality(LMI). Furthermore, we show that the state feedback $H^{\infty}$ controllers can be obtained from solutions satisfying LMI.

• Journal of the Optical Society of Korea
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• v.15 no.3
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• pp.232-236
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• 2011

We analyze the linear equalizers used in optically amplified on-off-keyed (OOK) systems to combat chromatic dispersion (CD) and polarization mode dispersion (PMD), and we derive the mathematical minimum mean squared error (MMSE) performance of these equalizers. Currently, the MMSE linear equalizer for optical OOK systems is obtained by simulations using adaptive approaches such as least mean squared (LMS) or constant modulus algorithm (CMA), but no theoretical studies on the optimal solutions for these equalizers have been performed. We model the optical OOK systems as square-law nonlinear channels and compute the MMSE equalizer coefficients directly from the estimated optical channel, signal power, and optical noise variance. The accuracy of the calculated MMSE equalizer coefficients and MMSE performance has been verified by simulations using adaptive algorithms.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.456-465
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• 2006

The problem of recursive filtering far linear discrete-time systems with uncertainties is considered. A new suboptimal filtering algorithm is herein proposed. It is based on the fusion formula, which represents an optimal mean-square linear combination of local Kalman estimates with weights depending on cross-covariances between local filtering errors. In contrast to the optimal weights, the suboptimal weights do not depend on current measurements, and thus the proposed algorithm can easily be implemented in real-time. High accuracy and efficiency of the suboptimal filtering algorithm are demonstrated on the following examples: damper harmonic oscillator motion and vehicle motion constrained to a plane.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.492-500
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• 2007

This paper focuses on the problem of guaranteed cost control for a class of uncertain linear delay systems with actuator failures. When actuators suffer "serious failure" the never failed actuators can not stabilize the system, based on switching strategy of average dwell time method, under the condition that activation time ratio between the system without actuator failure and the system with actuator failures is not less than a specified constant, a sufficient condition for exponential stability and weighted guaranteed cost performance are developed in terms of linear matrix inequalities (LMIs). Finally, as an example, a river pollution control problem illustrates the effectiveness of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.822-827
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• 2014

This paper presents a robust observer-based output feedback control for stabilization of linear time invariant systems with polytopic uncertainties. To this end, this paper not only finds a robust observer gain but also suggests how to determine the model used in the observer, which is not obvious due to model uncertainties in the conventional observer design method. The robust observer gain and the observer model are selected in a way that the whole closed-loop is stable by solving LMIs and BMIs (Linear Matrix Inequalities and Bilinear Matrix Inequalities). A simulation example shows that the proposed robust observer-based output feedback control successfully leads to closed-loop stability.