• 대한임베디드공학회논문지
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• 제12권4호
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• pp.223-229
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• 2017

An angle error is a factor obstructing to track accurate position in tracking radars. And the noise incurring the angle error can be divided as follows; thermal noise and glint. In general, Extended Kalman filter used in tracking radars is designed with considering thermal noise only. The Extended Klaman filter uses a fixed measurement error covariance when updating an estimate state by using ahead state and measurement. But, a noise power varies according to the range. Therefore we purposes the adaptive Kalman filter which changes the measurement noise covariance according to the range. In this paper, we compare the performance of the Extended Kalman filter and the proposed adaptive Kalman filter by considering KSLV-I (Korean Satellite Launch Vehicles).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
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• pp.41-43
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• 2004

This paper is concerned with attitude estimation using low cost, small-sized accelerometers and gyroscopes. A two step extended Kalman filter is proposed, which adaptively compensates external acceleration. External acceleration is the main source of estimation error. In the proposed filter, direction of external acceleration is estimated. According to the estimated direction, the accelerometer measurement covariance matrix of the two step extended Kalman filter is adjusted. The proposed algorithm is verified through experiments.

• 대한전기학회논문지
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• 제36권12호
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• pp.908-917
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• 1987

Most of moving targets are modelled as nonlinear dynamic equations. In recent years, the extended Kalman filter is frequently used for estimating their behaviors. The conditional Gaussian filter is more suitable than extended kalman filter in the filtering problem of nonlinear systems. But extended Kalman filter and conditional Gaussian filter often do not give optimal estimates and fail to track target trajectories because of its properties. Therefore it is desirable to use adaptive techniques to adapt target maneuvers. In this paper, we will discuss adaptive filtering technique using innovation process based on extended Kalman filter in real time, and suggest another maneuver estimation method using MRAS technique.

• International Journal of Aeronautical and Space Sciences
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• 제3권2호
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• pp.88-94
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• 2002

This paper describes attitude determination algorithm for the low earth orbit(LEO) spacecraft using stellar inertial sensors. The cascaded gyro/star tracker extended Kalman filter is constructed to fuse two sensor data. And then the smoothing of the measurement are proposed for an unreasonable jump of star tracker. The smoothing algorithm for the rejection of star tracker error jumps is designed by scalar adaptive filter. The proposed algorithms operate to process the measurement of gyro/star tracker Kalman filter, therefore, it is comparatively simple to apply these methods to other integration systems. Simulations to gyro/star tracker integrated system show that the proposed method is effective.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1016-1026
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• 2017

An adaptive extended Kalman filter based on the maximum likelihood (EKF-ML) is proposed for detecting voltage sag in this paper. Considering that the choice of the process and measurement error covariance matrices affects seriously the performance of the extended Kalman filter (EKF), the EKF-ML method uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. This can ensure that the EKF has better accuracy and faster convergence for estimating the voltage amplitude (states). Moreover, without more complexity, the EKF-ML algorithm is almost as simple as the conventional EKF, but it has better anti-disturbance performance and more accuracy in detection of the voltage sag. More importantly, the EKF-ML algorithm is capable of accurately estimating the noise parameters and is robust against various noise levels. Simulation results show that the proposed method performs with a fast dynamic and tracking response, when voltage signals contain harmonics or a pulse and are jointly embedded in an unknown measurement noise.

• 한국전산구조공학회논문집
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• 제32권1호
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• pp.45-54
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• 2019

본 논문에서는 EKF기법의 초기 파라미터 설정에 따른 상태벡터의 발산 문제를 해결하고자 AEKF기법을 제시한다. EKF기법의 초기 파라미터는 상태벡터 수렴 및 안정성에 중요한 역할을 함으로 초기 파라미터의 적절한 설정은 EKF를 사용함에 있어 매우 중요하다. AEKF방법은 초기 파라미터인 P행렬을 k스텝마다 업데이트하여 초기 상태벡터의 변화에 민감하게 반응할 수 있으며, 또한 초기 상태벡터와 실제 시스템 모델과의 차이가 크게 발생하여도 적응적으로 P행렬의 값을 조절하여 상태벡터의 수렴을 가능하게 한다. 또한 Q행렬 및 R행렬을 k스텝 업데이트하여 상태벡터의 수렴 안정성을 더욱 확보하였다. 3DOF시스템을 통해서 AEKF기법의 결과와 EKF, UKF기법을 비교 검증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.510-513
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• 1986

In recent years the Kalman filter(extended Kalman filter) have been applied to a wide variety of tracking moving targets, because of its properties. For such a reason, in this paper we attempt to study on adaptive filter algorithms which estimate unknown bias maneuvering inputs.

• 상하수도학회지
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• 제20권6호
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• pp.829-836
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• 2006

The reaction rate of denitrification is primarily affected by the utilization of organics that are usually limited in the anoxic period in a sequencing batch reactor. It is necessary to add an extemal carbon source for sufficient denitrification. An adaptive model of state-space based on the extended Kalman filter is applied to manipulate the dosage rate of extemal carbon automatically. Control strategies for denitrification have been studied to improve control performance through simulations. The normal control strategy of the constant set-point results in the overdosage of external carbon and deterioration of water quality. To prevent the overdosage of external carbon, improved control strategies such as the constrained control action, variable set-point, and variable set-point after dissolved oxygen depletion are required. More stable control is obtained through the application of the variable set-point after dissolved oxygen depletion. The converging value of the estimated denitrification coefficient reflects conditions in the reactor.

• International Journal of Control, Automation, and Systems
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• 제2권3호
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• pp.310-318
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• 2004

In this paper, an unscented Kalman filter (UKF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, an UKF is used because of the drawbacks of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

• 한국전자통신학회논문지
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• 제7권6호
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• pp.1413-1422
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• 2012

비선형 적응백스텝핑 제어기법은 외부 환경에 의한 여러가지 파라미터의 변동에도 불구하고 강인한 특성을 가진다. 이를 사용하여 IPMSM(Interior Permanent Magnet Synchronous Motor)의 정밀한 속도제어기를 설계하기 위해서는 빠른 제어 주기를 가져야만 한다. 하지만 속도 측정을 위한 엔코더의 분해능의 제약으로 연산주기를 빠르게 가져가지 못하고, 결국 제어기의 성능을 높이지 못하게 된다. 본 논문은 빠르고 정밀한 속도 제어기를 설계하기 위하여 비선형 적응백스텝핑 제어기법을 적용한 센서리스 속도 제어기 설계 방법을 제안한다. 제어기는 EKF(Extended Kalman Filter)를 이용하여 추정된 속도정보를 이용하여 비선형 적응백스텝핑 제어기법을 사용하는 방식으로 IPMSM의 속도 제어를 수행한다. 제안된 제어기의 성능은 PSIM을 이용한 모의 실험을 통하여 검증하였다.