• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.494-496
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• 1999

In this paper, we consider the design of a state feedback $H_{\infty}$ controller for uncertain linear systems with saturating actuators. We consider a general saturating actuator and employ the additive decomposition to deal with it effectively. And the considered uncertainty is the unstructured uncertainty which is only known its norm bound. Based on Linear Matrix Inequality(LMI) techniques, we present a condition on designing a controller that guarantees the $L_2$ gain, from the noise to the output, is not greater than a given value. A controller is obtained by checking the feasibility of three LMI's, and this can be easily done by well-known control package. Finally, we show the usefulness of our result by a numerical example.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.779-782
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• 1996

Repetitive control is a proposed control strategy in view of the internal model principle and achieves a high accuracy asymptotic tracking property by implementing a model that generates the periodic signals of period into the closed-loop system. Since the repetitive control system contains a periodic signal generator with positive feedback loop, which reduces the stability margin, in the overall closed-loop system, the stability of the closed-loop system should be considered as an important problem. In case that a real system has plant uncertainties which are not represented through modeling, the robust stability problem of the repetitive control system has not been considered sufficiently. In this paper, we propose the robust stability condition for the system with modeling uncertainty. The proposed robust stability condition will be obtained using the robust performance condition in the H$_{\infty}$ control. Moreover, by use of the proposed robust stability condition, we propose a procedure that designs a repetitive controller and a feedback controller simultaneously which can stabilize the overall closed-loop system robustly and which can also do the closedloop system without repetitive controller..

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.575-580
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• 1992

Mixed H$_{2}$/H$_{\infty}$ robust control synthesis is considered for finite dimensional linear time-invariant systems under the presence of diagonal structured uncertainties. Such uncertainties arise for instance when there is real perturbation in the nominal model of the state space system or when modeling multiple (unstructured) uncertainty at different locations in the feedback loop. This synthesis problem is reduced to convex optimization problem over a bounded subset of matrices as well as diagonal matrix having certain structure. For computational purpose, this convex optimization problem is further reduced into Generalized Eigenvalue Minimization Problem where a powerful algorithm based on interior point method has been recently developed..

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.356-359
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• 1995

This paper uses a new method to improve the performance criterion of an active suspension car. The used control strategy is based on robust H$_{\infty}$ control theory taking into consideration the chasis flexibility. It will be shown that the modeling errors can be lumped into an unstructured uncertainty and the robust controller designed in the presence of these perturbations could maintain the stability and performance even for the controlled true system..

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.449-451
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• 1998

In this paper, we consider the problem of the robust stability of uncertain linear systems with multiple time-varying delays. The considered uncertainties are both the unstructured uncertainty which is only known its norm bound and the structured uncertainty satisfying the matching conditions, respectively. We present conditions that guarantee the robust stability of systems based on Lyapunov stability theorem and $H_{\infty}$ theory in the time domain. Finally, we show the usefulness of our results by numerical examples.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.107-115
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• 2001

Most of rotating machineries supported by contact bearing accompany lowering efficiency, vibration and wear. Moreover, because of vibration, which is occurred in rotating shaft, they have the limits of driving speed and precision. The rotor system has parametric variations or external disturbances such as mass unbalance variations in long operation. Therefore, it is necessary to research about magnetic bearing, which is able to support the shaft without mechanical contact and to control rotor vibration without being affected by external disturbances or parametric changes. Magnetic bearing system in the paper is composed of position sensor, digital controller, actuating amplifier and electromagnet. This paper applied the robust control method using quantitative feedback theory (QFT) to control the magnetic bearing. It also proposed design skill of optimal controller, in case the system has structured uncertainty, unstructured uncertainty and disturbance. Reduction of vibration is verified at critical rotating speed even external disturbance exists. Unbalance response, a serious problem in rotating machinery, is improved by magnetic bearing using QFT algorithm.

• Smart Media Journal
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• v.10 no.2
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• pp.16-21
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• 2021

Financial time series analysis plays a very important role economically and socially in modern society and is an important task affecting global development, but due to difficulties such as a lot of noise and uncertainty, financial time series analysis prediction is a difficult research topic. In this paper, we propose a market prediction method (MPIL) by converting unstructured data and structured data into images. For market prediction, it analyzes SNS and news data, which is unstructured data for n days, and converts the market data, which is structured data, to an image with the GADF algorithm, and predicts an ultra-short market that predicts the price of n+1 days through image learning. MPIL has an average accuracy of 56%, which is higher than the 50% average accuracy of the model that predicts the market with LSTM by using sentiment analysis used for existing market forecasting.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.3
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• pp.97-105
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• 1997

The aim of this paper is to introduce a design technique of the Two-Degree-of-Freedom(TDF) satellite-tracking control system which has not only the robust stability for a unstructured uncertainty but also the robust performance for a structured uncertainty. This TDF system which can design the feedforward controller KI and the feedback one K independently is designed by , $\mu$-synthesis. The effectiveness of this TDF system is verified and compared with the One-Degree-of -Freedom(ODF) satellitetracking control system by computer simulation.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.608-613
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• 2017

In this paper, we consider the stability bound for uncertainty of delayed state variables in the linear discrete interval time-varying systems with time-varying delay time. The considered system has an interval time-varying system matrix for non-delayed states and is perturbed by the unstructured time-varying uncertainty in delayed states with time-varying delay time within fixed interval. Compared to the previous results which are derived for time-invariant cases and can not be extended to time-varying cases, the new stability bound in this paper is applicable to time-varying systems in which every factors are considered as time-varying variables. The proposed result has no limitation in applicable systems and is very powerful in the aspects of feasibility compared to the previous. Furthermore. the new bound needs no complex numerical algorithms such as LMI(Linear Matrix Inequality) equation or upper solution bound of Lyapunov equation. By numerical examples, it is shown that the proposed bound is able to include the many existing results in the previous literatures and has better performances in the aspects of expandability and effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1816-1819
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• 1997

Using the vision system, robotic tasks in unstructured environments can be accompished, which reduces greatly the cost and steup time for the robotic system to fit to he well-defined and structured working environments. This paper proposes a dynamic control scheme for robot manipulator with eye-in-hand camera configuration. To perfom the tasks defined in the image plane, the camera motion Jacobian (image Jacobian) matrix is used to transform the camera motion to the objection position change. In addition, the dynamic learning controller is designed to improve the tracking performance of robotic system. the proposed control scheme is implemented for tasks of tracking moving objects and shown to outperform the conventional visual servo system in convergence and robustness to parameter uncertainty, disturbances, low sampling rate, etc.