• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.349-351
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• 2004

The classical dynamic backpropagation learning algorithm has the problems of learning speed and the determine of learning parameter. The Extend Kalman Filter(EKF) is used effectively for a state estimation method for a non linear dynamic system. This paper presents a learning algorithm using Dual Extended Kalman Filter(DEKF) for Fully Recurrent Neural Network(FRNN). This DEKF learning algorithm gives the minimum variance estimate of the weights and the hidden outputs. The proposed DEKF learning algorithm is applied to the system identification of a nonlinear SISO system and compared with dynamic backpropagation learning algorithm.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.158-163
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• 2013

The fusion of the GPS (Global Positioning System) and DR (Dead Reckoning) is widely used for position and latitude estimation of vehicles such as a mobile robot, aerial vehicle and marine vehicle. Among the many types of aerial vehicles, grater focus is given on the quad-rotor and accuracy of the position information is becoming more important. In order to exactly estimate the position information, we propose the fusion method of GPS and Gyroscope sensor using the DEKF (Dual Extended Kalman Filter). The DEKF has an advantage of simultaneously estimating state value and a parameter of dynamical system. It can also be used even if state value is not available. In order to analyze the performance of DEKF, the computer simulation for estimating the position, the velocity and the angle in a circle trajectory of quad-rotor was done. As it can be seen from the simulation results using own proposed DEKF instead of EKF on own fusion method in the navigation of a quad-rotor gave better performance values.

• 한국항공우주학회지
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• 제37권12호
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• pp.1225-1231
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• 2009

인공위성의 반작용 휠 클러스터는 보통 4개의 반작용 휠로 구성이 된다. 각각의 반작용 휠은 인공위성의 자세 축과 일치하게 배치되지 않기 때문에 하나의 반작용 휠에 고장이 일어난 경우 반작용 휠 자체의 센서를 이용한 방법 외에는 고장 분리가 매우 어렵다. 본 논문에서는 이중 필터를 이용하여 고장 검출에 효과적인 파라미터를 구성하고, 인공위성의 반작용 휠 각각이 정지 고장을 일으킬 경우를 가정하여 이중 필터와 다중 가설 필터를 이용하여 반작용 휠의 고장분리기를 설계하였다. 또한 이를 4개의 반작용 휠로 자세제어가 이루어지는 인공위성 시스템에 적용한 시뮬레이션으로 고장 검출 및 분리 성능이 향상되는 것을 검증하였다.

• Journal of Power Electronics
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• 제12권1호
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• pp.1-9
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• 2012

This study investigates an application of the Hamming network-dual extended Kalman filter (DEKF) based on pattern recognition for high accuracy state-of-charge (SOC)/capacity estimation and state-of-health (SOH) prediction at various temperatures. The averaged nine discharging/charging voltage-temperature (DCVT) patterns for ten fresh Li-Ion cells at experimental temperatures are measured as representative patterns, together with cell model parameters. Through statistical analysis, the Hamming network is applied to identify the representative pattern that matches most closely with the pattern of an arbitrary cell measured at any temperature. Based on temperature-checking process, model parameters for a representative DCVT pattern can then be applied to estimate SOC/capacity and to predict SOH of an arbitrary cell using the DEKF. This avoids the need for repeated parameter measuremet.

• 한국융합학회논문지
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• 제9권6호
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• pp.53-60
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• 2018

본 논문은 듀얼 확장 칼만 필터를 기반으로 2링크 매니퓰레이터의 정밀한 제어를 위한 미지 변수 추정법을 제안한다. 2링크 매니퓰레이터 시스템은 기구학 및 동역학 방정식에 비선형성을 가지며 내부 파라미터의 변화에 민감한 특성을 보인다. 이러한 시스템의 경우 내부 미지 파라미터의 추정이 매우 중요하다. 특히 거친 환경에서 작업을 수행함에 있어서 중량과 관성행렬의 변화는 시스템을 불안정하게 만드는 요소이다. 따라서 본 논문에서 제안한 방법을 기반으로 시스템의 상태 및 미지 변수를 동시에 추정하여 앞서 소개한 문제점들을 해결하고자 한다. 제안한 방법은 Mathwork에서 제공하는 Matlab 기반으로 시뮬레이션을 수행했고, 그 결과는 RLS 알고리즘과 비교하여 성능을 분석하였다. 제안된 방법은 상태 및 미지 변수 추정에 RLS 방법보다 뛰어난 추정 성능을 보임을 확인 하였다.

• Journal of Power Electronics
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• 제16권1호
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• pp.238-248
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• 2016

The state-of-charge (SOC) and state-of-health (SOH) estimation of batteries play important roles in managing batteries for automotive applications. However, an accurate state estimation of a battery is difficult to achieve because of certain factors, such as measurement noise, highly nonlinear characteristics, strong hysteresis phenomenon, and diffusion effect of batteries. In certain vehicular applications, such as idle stop-start systems (ISSs), significant errors in SOC/SOH estimation may lead to a failure in restarting a combustion engine after the shut-off period of the engine when the vehicle is at rest, such as at a traffic light. In this paper, a dual extended Kalman filter algorithm with a dynamic equivalent circuit model of a lead-acid battery is proposed to deal with this problem. The proposed algorithm adopts a battery model by taking into account the hysteresis phenomenon, diffusion effect, and parameter variations for accurate state estimations of the battery. The validity of the proposed algorithm is verified through experiments by using an absorbed glass mat valve-regulated lead-acid battery and a battery sensor cable for commercial ISS vehicles.

• International Journal of Control, Automation, and Systems
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• 제5권4호
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• pp.388-396
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• 2007

This paper describes a multipath estimation method for Global Positioning System (GPS) dual frequency carrier phase measurements. Multipath is a major error source in high precision GPS applications, i.e., carrier phase measurements for precise positioning and attitude determinations. In order to estimate and remove multipath at carrier phase measurements, an array GPS antenna system has been used. The known geometry between the antennas is used to estimate multipath parameters. Dual frequency carrier phase measurements increase the redundancy of measurements, so it can reduce the number of antennas. The unscented Kalman filter (UKF) is recently applied to many areas to overcome some of the limitations of the extended Kalman filter (EKF) such as weakness to severe nonlinearity. This paper uses the UKF for estimating multipath parameters. A series of simulations were performed with GPS antenna arrays located on a straight line with one reflector. The geometry information of the antenna array reduces the number of estimated multipath parameters from four to three. Both the EKF and the UKF are used as estimation algorithms and the results of the EKF and the UKF are compared. When the initial parameters are far from true parameters, the UKF shows better performance than the EKF.

• Journal of Power Electronics
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• 제17권2호
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• pp.398-410
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• 2017

This work presents the design of a dual extended Kalman filter (EKF) as a state/parameter estimator suitable for adaptive state-of-charge (SoC) estimation of an automotive lithium-iron-phosphate ($LiFePO_4$) cell. The design of both estimators is based on an experimentally identified, lumped-parameter equivalent battery electrical circuit model. In the proposed estimation scheme, the parameter estimator has been used to adapt the SoC EKF-based estimator, which may be sensitive to nonlinear map errors of battery parameters. A suitable weighting scheme has also been proposed to achieve a smooth transition between the parameter estimator-based adaptation and internal model within the SoC estimator. The effectiveness of the proposed SoC and parameter estimators, as well as the combined dual estimator, has been verified through computer simulations on the developed battery model subject to New European Driving Cycle (NEDC) related operating regimes.

• 한국측량학회지
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• 제27권4호
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• pp.461-467
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• 2009

상대측위 기법은 공통오차를 제거 또는 감소하여 상대적으로 높은 위치정확도를 얻을 수 있기 때문에 주로 고정밀 GPS 위치정보 생성에 사용된다. 본 연구에서는 높은 위치정밀도를 산출할 수 있는 RTK 알고리즘을 개발하였고, 또한 매 관측시간별로 위치정보와 모호정수를 추정할 수 있도록 필터를 구성하였다. 상태 변수 추정을 위해 확장칼만필터를 사용하였고, 모호정수 결정을 위해 Modified LAMBDA 방법이 고려되었다. 자료처리는 단기 선에서 GPS 단일주파수와 이중주파수를 이용하여 다양한 측위를 수행하였다. 측위결과에 대한 검증절차는 Bernese 5.0 소프트웨어의 결과와 비교하였고, 각 위치오차에 대한 통계값과 모호정수 결정율을 제시하였다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2007년도 추계학술대회 논문집
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• pp.60-62
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• 2007

The open circuit voltage (OCV) is widely used to estimate the state of charge (SOC) in many estimation algorithms. However, the relationship between the OCV and SOC can not be exactly same for all batteries. Because the conventional OCV-SOC differs between batteries, there is a problem that the relationship of the OCV-SOC should be measured to accurately estimate the SOC. Therefore, the conventional OCV-SOC is modified to a new relationship in this paper. Thus, problems resulting from the defects of the extended Kalman filter (EKF) can be avoided by preventing the relationship from varying. In this paper, SOC and capacity of the lithium-ion battery are estimated using the dual EKF with the proposed method.