• 제목/요약/키워드: Dual Kalman Filter

검색결과 35건 처리시간 0.026초

Dual Kalman Filter를 이용한 G/R 비의 실시간 결정 (Real-time Decision of G/R Ratio using the Dual Kalman Filter)

  • 유철상;김정호
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2011년도 학술발표회
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    • pp.353-356
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    • 2011
  • 본 연구에서는 G/R 비의 실시간 결정을 목적으로 Dual Kalman Filter를 이용하였다. Dual Kalman Filter 는 이중추정(dual estimation)을 기반으로 하는 자료동화기법으로 기존 Kalman Filter와 상이한 상태-공간 모형으로 구성된다. 이에 Dual Kalman Filter와 기존 Kalman Filter의 적용성능을 비교 검토하였으며, 다양한 비교를 위하여 강우의 임계치와 누적시간의 고려여부에 따른 결과를 추가적으로 검토하였다. 두 기법의 적용성능 비교결과 Dual Kalman Filter가 우수한 것으로 나타났다. 이는 Dual Kalman Filter 기법이 G/R 비의 큰 변동성과 이상치를 효과적으로 필터링하고, 시계열 모형의 매개변수를 실시간으로 갱신하여 정확한 예측치를 추정하였기 때문인 것으로 판단된다.

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듀얼칼만필터를 이용한 이중편파 레이더 강우의 실시간 편의보정 (Real-time bias correction of Beaslesan dual-pol radar rain rate using the dual Kalman filter)

  • 나우영;유철상
    • 한국수자원학회논문집
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    • 제53권3호
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    • pp.201-214
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    • 2020
  • 본 연구에서는 듀얼칼만필터를 이용하여 이중편파 레이더 강우의 편의를 실시간으로 보정할 수 있는 방법을 제안하였다. 듀얼칼만필터는 기존의 칼만필터와 달리 두 개의 시스템(상태추정시스템, 모형추정시스템)이 동시에 가동되면서 실시간으로 상태변수가 예측된다. 강우강도 추정치에 보정계수를 적용함으로써 편의보정이 이루어지며, 보정계수는 듀얼칼만필터의 상태-공간모형에 의해 실시간으로 예측된다. 해당 기법을 2016년 7월에 발생한 지속시간이 긴 호우사상에 대해 적용하고 편의보정 결과를 평가하였다. 먼저, 보정계수는 대부분 1과 2 사이의 값으로 산정되어 지상관측 강우강도보다 레이더 강우강도가 약간 과소추정되는 경향을 보였다. 보정계수에 대한 시계열을 설명할 수 있는 모형으로는 AR(1) 모형이 적합한 것으로 확인되었다. 아울러 듀얼칼만필터로 예측한 보정계수는 관측된 자료를 이용하여 산정한 보정계수와 유사한 경향을 가지는 것으로 나타났다. 칼만필터와의 비교 결과, 보정계수의 변동성이 커질수록 듀얼칼만필터가 칼만필터에 비해 우수한 예측 성능을 가지는 것으로 확인되었다. 본 연구를 통해 강우의 변동성이 크고, 지속시간이 긴 호우사상에 대한 듀얼칼만필터의 적합성이 검증되었다.

두개의 Extended Kalman Filter를 이용한 Recurrent Neural Network 학습 알고리듬 (A Learning Algorithm for a Recurrent Neural Network Base on Dual Extended Kalman Filter)

  • 송명근;김상희;박원우
    • 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.

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Kalman Randomized Joint UKF Algorithm for Dual Estimation of States and Parameters in a Nonlinear System

  • Safarinejadian, Behrouz;Vafamand, Navid
    • Journal of Electrical Engineering and Technology
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    • 제10권3호
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    • pp.1212-1220
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    • 2015
  • This article presents a new nonlinear joint (state and parameter) estimation algorithm based on fusion of Kalman filter and randomized unscented Kalman filter (UKF), called Kalman randomized joint UKF (KR-JUKF). It is assumed that the measurement equation is linear. The KRJUKF is suitable for time varying and severe nonlinear dynamics and does not have any systematic error. Finally, joint-EKF, dual-EKF, joint-UKF and KR-JUKF are applied to a CSTR with cooling jacket, in which production of propylene glycol happens and performance of KR-JUKF is evaluated.

듀얼 확장 칼만 필터를 이용한 쿼드로터 비행로봇 위치 정밀도 향상 알고리즘 개발 (Precise Positioning Algorithm Development for Quadrotor Flying Robots Using Dual Extended Kalman Filter)

  • 승지훈;이덕진;류지형;정길도
    • 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.

출력 시간 지연 시스템의 루우프 복구특성 (LTR properties for output-delayed systems)

  • 이상정;홍석민
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.161-167
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    • 1993
  • This paper presents robustness properties of the Kalman Filter ad the associated LQG/LTR method for linear time-invariant systems having delays in both the state and output. A circle condition relating to the return difference matrix associated with the Kalman filter is derived. Using this circle condition, it is shown that the Kalman filter guarantees(1/2, .inf.) gain margin and .+-.60.deg. phase margin, which are the same as those for nondelay systems. However, it is shown that, even for minimum phase plants, the LQG/LTR method can not recover the target loop transfer function. Instead, an upper bound on the recovery error is obtained using an upper bound of the solution of the Kalman filter Riccati equations. Finally, some dual properties between output-delated system and input-delayed systems are exploited.

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이중 필터와 다중 가설 확장 칼만 필터를 적용한 인공위성 반작용 휠의 고장 분리기 설계 (Design of Fault Isolator of Satellite Reaction Wheel System Using Dual Filter and Multi-hypothesis Extended Kalman Filter)

  • 최광록;박찬국
    • 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.

Parameter Estimation for Multipath Error in GPS Dual Frequency Carrier Phase Measurements Using Unscented Kalman Filters

  • Lee, Eun-Sung;Chun, Se-Bum;Lee, Young-Jae;Kang, Tea-Sam;Jee, Gyu-In;Kim, Jeong-Rae
    • 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.

Discharging/Charging Voltage-Temperature Pattern Recognition for Improved SOC/Capacity Estimation and SOH Prediction at Various Temperatures

  • Kim, Jong-Hoon;Lee, Seong-Jun;Cho, Bo-Hyung
    • 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.

Evaluation of RTK Methods for Moving Vehicles and Practical Recommendations

  • Kim, Sae-Kyeol;Kim, Euiho
    • Journal of Positioning, Navigation, and Timing
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    • 제10권4호
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    • pp.253-262
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    • 2021
  • Global Navigation Satellite Systems (GNSS) based precise positioning using Real Time Kinematic (RTK) technique has been proposed as an enabler of the formation operation of moving vehicles. In RTK methods, the integer ambiguity of GNSS carrier phase measurements must be resolved. Although there have been many proposed algorithms for the integer ambiguity resolution, the widelane combination of carrier phase measurements and LAMBDA methods have gained the most popularity in literatures when dual frequency GNSS measurements were used. In this paper, we evaluated five alternative methods to determine relative positions of moving base and rover receivers; the round-off scheme of widelane carrier phase, instant least-squares and Kalman filter-based LAMBDA with widelane carrier phase, instant least-squares and Kalman filter-based LAMBDA with dual frequency measurements. The paper presented the performance of each method using flight test data, which showed their strength and weakness in the aspects of time-to-first-fix, ambiguity resolution success ratio, and relative position errors. Based on that, we provided practical recommendations of RTK operations for moving vehicles.