• International Journal of Naval Architecture and Ocean Engineering
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• 제6권3호
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• pp.626-637
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• 2014

On ship, especially on large ship, the flexure deformation between Master (M)/Slave (S) Inertial Navigation System (INS) is a key factor which determines the accuracy of the integrated system of M/S INS. In engineering this flexure deformation will be increased with the added ship size. In the M/S INS integrated system, the attitude error between MINS and SINS cannot really reflect the misalignment angle change of SINS due to the flexure deformation. At the same time, the flexure deformation will bring the change of the lever arm size, which further induces the uncertainty of lever arm velocity, resulting in the velocity matching error. To solve this problem, a $H_{\infty}$ algorithm is proposed, in which the attitude and velocity matching error caused by deformation is considered as measurement noise with limited energy, and measurement noise will be restrained by the robustness of $H_{\infty}$ filter. Based on the classical "attitude plus velocity" matching method, the progress of M/S INS information fusion is simulated and compared by using three kinds of schemes, which are known and unknown flexure deformation with standard Kalman filter, and unknown flexure deformation with $H_{\infty}$ filter, respectively. Simulation results indicate that $H_{\infty}$ filter can effectively improve the accuracy of information fusion when flexure deformation is unknown but non-ignorable.

• 한국항공우주학회지
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• 제42권11호
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• pp.937-946
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• 2014

본 논문에서는 단일 틸트윙 무인기의 시스템 식별기법과 결과를 제시하였다. 주파수 영역의 시스템 식별 기법인 Modified Equation Error Method(MEEM)와 시간 영역의 시스템 식별 기법인 확장 칼만 필터(Extended Kalman Filter, EKF)를 사용하였다. 시스템 식별 기법의 검증을 위해 단일 틸트윙 방식 무인기인 CNUX-3의 모델을 통해 획득한 수직모드의 선형 시뮬레이션 결과에 센서 특성을 반영한 노이즈를 합성하여 가상의 비행데이터를 생성했다. 설계 변수의 변화에 따른 MEEM의 시스템 식별 성능 변화를 분석하였다. 또한 고정밀 푸리에 변환(High accuracy Fourier Transform)을 MEEM에 적용하여 정확도를 향상시켰다. MEEM과 EKF의 시스템 식별 결과를 비교하고, 최상의 성능지수를 갖는 설계 변수값과 초기값을 최적화를 통해 결정하였다.

• 한국항공우주학회지
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• 제44권4호
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• pp.298-307
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• 2016

인공위성의 자세추정은 결정론적 방법과 재귀적인 방법으로 나눌 수 있는데, 이 중 재귀적인 방법으로는 칼만 필터를 사용하여 자세를 추정하는 알고리즘이 널리 사용되고 있다. 초소형 큐브 위성의 경우 많은 탑재체를 실을 수 없기에 최소한의 자세 센서만을 이용해야 하는 제한점이 있다. 미션에 따라 식 기간 및 태양 센서의 데이터 이용이 불가능할 때에도 인공위성의 자세추정은 계속 되어야 인공위성은 임무를 성공적으로 완수할 수 있게 된다. 본 연구에서는 일반적인 인공위성의 자세추정 기법을 기반으로 큐브위성의 동역학과 토크외란을 고려하여 알고리즘을 발전시켜 식 기간에서도 더욱 정확한 자세 추정이 가능하도록 하였다. 제안된 알고리즘은 시뮬레이션을 통해 기존의 자세추정 방법과 비교하여 그 성능을 검증하였다. 또한 위성체가 우주 환경에서 운용되면서 받을 수 있는 다양한 크기의 토크외란에 따른 자세추정 오차를 분석하였다.

• Journal of Power Electronics
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• 제18권1호
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• pp.234-250
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• 2018

This paper presents a new load sharing control for use between paralleled three-phase inverters in an islanded microgrid based on the online line impedance estimation by the use of a Kalman filter. In this study, the mismatch of power sharing when the line impedance changes due to temperature, frequency, significant differences in line parameters and the requirements of the Plug-and-Play mode for inverters connected to a microgrid has been solved. In addition, this paper also presents a new droop control method working with the line impedance that is different from the traditional droop algorithm when the line impedance is assumed to be pure resistance or pure inductance. In this paper, the line impedance estimation for parallel inverters uses the minimum square method combined with a Kalman filter. In addition, the secondary control loops are designed to restore the voltage amplitude and frequency of a microgrid by using a combined nominal value SOGI-PLL with a generalized integral block and phase lock loop to monitor the exact voltage magnitude and frequency phase at the PCC. A control model has been simulated in Matlab/Simulink with three voltage source inverters connected in parallel for different ratios of power sharing. The simulation results demonstrate the accuracy of the proposed control method.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2003년도 춘계전력전자학술대회 논문집(2)
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• pp.644-647
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• 2003

The predictive maintenance can help to avoid the serious plant breakdowns and catastrophies. This paper deals with the fault diagnosis of the rotor of the induction motor which is widely used in the plants. In order to detect the broken bar, the Extended Kalman Filter is adopted to estimate the rotor resistance on the base of model-based method. The proposed estimation method is simulated with the aid of Matlab.

• Journal of Astronomy and Space Sciences
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• 제10권1호
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• pp.1-16
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• 1993

Three typer of spin-axis attitude determination program for the geosynchronous transfer orbit spacecraft are developed. Deterministic closed-from algorithm, batch least-square algorithm and stabilized Kalman filter algorithm are used for implemetation of three programs. EUROSTAR bus model from British Aerospace is used for attitude sensor modelling. Attitude determinations using three programs are performed for the simulated sensor data according to INMARSAT 2-F1 prelaunch mission analysis.

• 제어로봇시스템학회논문지
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• 제6권11호
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• pp.1022-1032
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• 2000

We propose a sliding mode controller tracking the states of a time-varying reference model. The reference model generates the desired trajectories of the states, and the sliding mode controller regulates robustly the errors between the desired states and the measured states. We apply this controller to the overhead crane. Its reference model generates the trajectories of the damped-out swing angle and the swing angular velocity to suppress the swinging motion caused by the acceleration and the deceleration of crane transportation. Also, this model generates the desired trajectories of the position and velocity of the crane. The crane model is identified from the experimental data using an orthogonal function. Kalman filtering is applied to estimate the crane states. The designed controller is simulated on a computer and is tested through a 2-ton industrial overhead crane using the vector-controlled servo motor system. It is verified that, from the simulated and experimental results, the sliding mode controller tracking a time-varying reference model works well.

• Journal of Electrical Engineering and Technology
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• 제2권4호
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• pp.445-451
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• 2007

Voltage quality problems such as voltage sag, swell, flicker, undervoltage, and overvoltage have been of great concern for both utilities and customers over the last decade. In this paper, a new approach based on the $H_{\infty}$ algorithm to monitor voltage disturbances is presented. The key idea of this approach is to estimate the amplitude of the fundamental component of distorted and noisy voltage waveform instantaneously, and then the information can be extracted from the estimated envelope to identify and classify different voltage related power quality problems. The $H_{\infty}$ algorithm is characterized by a fast tracking, unlike that of existing techniques. The $H_{\infty}$ algorithm outperforms the Kalman Filter (KF) by its fast convergence and robust tracking performance against non-Gaussian noise. The paper investigates the effects of various types of noise on the performance of the $H_{\infty}$ algorithm. Digital simulation results confirm the validity and accuracy of the proposed method. The proposed $H_{\infty}$ algorithm is examined by tracking the flicker produced by a resistance welder simulated in the PSCAD/EMTDC package.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.484-487
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• 1995

An interacting multiple model (IMM) approach which merges two hypotheses for the situations of constant speed and constant acceleration model is considered for the tracking of maneuvering target. The inflexibility of uncertainty which lies in the kinematic constraint (KC) represented by pseudomeasurement noise variance is compensated by the mixing of estimates from two model Kalman tracker: one with KC and one without KC. The numerically simulated tracking performance is compared for the "great circular like turning" trajectory maneuver by the single model tracker with constant speed KC and two model tracker which is developed in this paper.his paper.

• 한국농공학회지
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• 제36권2호
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• pp.79-87
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• 1994

A real-time flood forecasting system(FLOFS) was developed for the real-time and predictive determination of flood discharges and stages, and to aid in flood management decisions in the Keum River Estuary Dam. The system consists of three subsystems : data subsystem, model subsystem, and user subsystem. The data subsystem controls and manages data transmitted from telemetering systems and simulated by models. The model subsystem combines various techniques for rainfall-runoff modeling, tidal-level forecasting modeling, one-dimensional unsteady flood routing, Kalman filtering, and autoregressivemovingaverage(ARMA) modeling. The user subsystem in a menu-driven and man-machine interface system.