• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.92-94
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• 2007

This paper considers an optimal control problem for a remote control to an electrical drive system with a DC motor. Since it is a linear control system with time-delay subject to unknown but bounded disturbance, we construct a worst-case feedback control policy. This policy can guarantee that, for all admissible uncertain disturbances, the real system state should be in a prescribed neighborhood of a desired value, and the cost functional takes the best guarantee value. The worst-case feedback control policy is allowed to be corrected at one correction point between the initial to the final time, which is equivalent to solving a 1-level min-max problem. Since the min-max problem at the stage does not yield a simple analytical solution, we consider an approximate control policy, which is equivalent and can be solved explicitly m the numerical experiments.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.649-651
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• 2015

This paper describes a robust adaptive sliding mode control (RASMC) for torque ripple minimization of switched reluctance motor (SRM) using it in automotive application. The objective is to control effort smoothness while the system is under perturbations by unstructured uncertainties, unknown parameters and external disturbances. The control algorithm employs an adaptive approach to remove the need for prior knowledge within the bound of perturbations. This is suitable for tackling the chattering problem in the sliding motion of sliding mode control method. The algorithm then incorporates modifications in order to build a chattering-free modified robust adaptive sliding mode control using Lyapunov stability theory.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2616-2628
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• 1994

Recently the Time Delay Control(TDC) method has been proposed as a promising technique in the robust control area, where the plant has unknown dynamics with parameter variations and substantial disturbances are present. When TDC is applied to the plant with saturation nonlinearity, however, the so called windup phenomena are observed to arise, causing excessive overshoot and instability. In order to solve this problem, we have proposed an anti-windup method for TDC. The stability of the overall system has been analyzed for a class of LTI MIMO system. The effectiveness for the proposed method has been shown with simulation and experiment results.

• Clinical and Experimental Pediatrics
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• v.59 no.sup1
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• pp.145-148
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• 2016

Takayasu arteritis (TA) is a chronic inflammatory disease of unknown etiology that affects mainly the aorta, main aortic branches, and pulmonary arteries. Diverse neurological manifestations of TA have rarely been reported in children. Posterior reversible encephalopathy syndrome (PRES) is a neuroradiological condition that presents with headache, seizure, visual disturbances, and characteristic lesions on imaging. Inflammatory condition and severe hypertension in TA can cause PRES. We report of a 5-year-old girl with presumed TA who presented with PRES and chronic total occlusion in the renal artery. The findings on magnetic resonance imaging suggested PRES. Left nephrectomy was performed for total occlusion of the left renal artery, and the confirmatory diagnosis of TA was based on the pathologic findings of the renal artery.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1584-1589
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• 2003

Simple and effectively developed learning control logic is used to control vibration of U type Tuned Liquid Damper system. The purpose of this paper is design optimal control system to deal with unknown errors from nonlinearity and variation that cost modeling difficulty in complex structure and is followed with the desired behavior. Finally this hybrid control method applied to U type Tuned Liquid Damper structure gives the benefit from better performance of precision and stability of the structure by reducing vibration effect. This research leads to safety design in various structure to robust unspecified foreign disturbances such as earthquake.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.153-158
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• 1999

We consider single-input nonlinear systems with unknown unmodelled time-varying parameters or disturbances which are bounded. The main goal is to identify classes of uncertain systems for which the control exist and to provide constructive design procedures. Assuming that the undisturbed nominal system ( ,g) is partially state feedback linearizable, that a strict triangularity condition, a linear parametrization condition, and {{{{ { G}_{r-1 } }}}} hold for the uncertain terms, and that some condition is satisfied in the transformed partially linear system, we design an adaptive regulating dynamic control. At first, we identify classes of nonlinear uncertain systems and give a systematic procedure for the design of a robust regulation for the nonlinear systems.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.130-130
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• 2000

This paper presents a robust fault diagnosis and fault tolerant control lot the actuator and sensor faults in the closed-loop systems affected by unknown inputs or disturbances. The fault diagnostic scheme is based on the residual set generation by using robust Parity space approach. Residual set is evaluated through the threshold test and then fault is isolated according to the decision logic table. Once the fault diagnosis module indicates which actuator or sensor is faulty, the fault magnitude is estimated by using the disturbance-decoupled optimal state estimation and a new additive control law is added to the nominal one to override the fault effect on the system. Simulation results show that the method has definite fault diagnosis and fault tolerant control ability against actuator and sensor faults.

• Journal of the Korean Statistical Society
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• v.27 no.3
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• pp.319-329
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• 1998

In the linear regression model with an autocorrelated disturbances, the Cochrane-Orcutt estimator (COE) is a well known alternative to the Generalized Least Squares estimator (GLSE). The efficiency of COE has been studied empirically in a Monte Carlo study when the unknown parameters are estimated by maximum likelihood method. In this paper, it is theoretically proved that the COE is shown to be inferior to the GLSE. The comparisons are based on the difference of corresponding information matrices or the ratio of their determinants.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.10
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• pp.918-922
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• 2007

Most of the study on system identification has been carried out using input/output relation in physical domain. However identification concept of stochastic system has not been reported up to now. Interest is focused to identify an unknown dynamic system under random external disturbances which is not possible to measure. A concept to identify the system parameters in stochastic domain is proposed and implemented in terms of simulation. Attempt has been made to identify the system parameters in inverse manner in stochastic domain based on system output only. Simulation is conducted to reveal quite noticeable performance of the proposed concept.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.414-417
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• 1997

We propose a decentralized $H_{\infty}$ state estimation method in the multisensor state estimation problem. The proposed method bounds the maximum energy gain from unknown external disturbances to the estimation errors in the suboptimal case. And we formulate the decentralized state estimation method in the general case of different global and local models using alternative gain equation of the $H_{\infty}$ state estimator which can calculate global state estimates from the the linear combination of local state estimates. In addition, the proposed update equation between global and local Riccati solutions can reduce unnecessary calculation burden efficiently.