• 제목/요약/키워드: external kalman filter

검색결과 90건 처리시간 0.029초

Substructural parameters and dynamic loading identification with limited observations

  • Xu, Bin;He, Jia
    • Smart Structures and Systems
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    • 제15권1호
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    • pp.169-189
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    • 2015
  • Convergence difficulty and available complete measurement information have been considered as two primary challenges for the identification of large-scale engineering structures. In this paper, a time domain substructural identification approach by combining a weighted adaptive iteration (WAI) algorithm and an extended Kalman filter method with a weighted global iteration (EFK-WGI) algorithm was proposed for simultaneous identification of physical parameters of concerned substructures and unknown external excitations applied on it with limited response measurements. In the proposed approach, according to the location of the unknown dynamic loadings and the partially available structural response measurements, part of structural parameters of the concerned substructure and the unknown loadings were first identified with the WAI approach. The remaining physical parameters of the concerned substructure were then determined by EFK-WGI basing on the previously identified loadings and substructural parameters. The efficiency and accuracy of the proposed approach was demonstrated via a 20-story shear building structure and 23 degrees of freedom (DOFs) planar truss model with unknown external excitation and limited observations. Results show that the proposed approach is capable of satisfactorily identifying both the substructural parameters and unknown loading within limited iterations when both the excitation and dynamic response are partially unknown.

SOC 추정을 위한 밀폐형 Flooded 연축전지의 히스테리시스 모델링 (Hysteresis Modeling of the Sealed Flooded Lead Acid Battery for SOC Estimation)

  • 압둘바싯칸;최우진
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2016년도 전력전자학술대회 논문집
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    • pp.309-310
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    • 2016
  • Sealed flooded lead acid batteries are becoming popular in the industry because of their low cost as compared to their counterparts. State of Charge (SOC) estimation has always been an important factor in battery management systems. For the accurate SOC estimation, open circuit voltage (OCV) hysteresis should be modelled accurately. The hysteresis phenomenon of the sealed flooded lead acid battery is discussed in detail and its ultimate modeling is proposed based on the conventional parallelogram method. The SOC estimation is performed by using Unscented Kalman Filter (UKF) while the parameters of the battery are estimated using Auto Regressive with external input (ARX) method. The validity of the proposed method is verified by the experimental results. The SOC estimation error by the proposed method is less than 3 % all wing the 125hr test.

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Robust State Estimation Based on Sliding Mode Observer for Aeroelastic System

  • Jeong In-Joo;Na Sungsoo;Kim Myung-Hyun;Shim Jae-Hong;Oh Byung-Young
    • Journal of Mechanical Science and Technology
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    • 제19권2호
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    • pp.540-548
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    • 2005
  • This paper concerns the application and demonstration of sliding mode observer for aeroelastic system, which is robust to model uncertainty including mass and stiffness of the system and various disturbances. The performance of a sliding mode observer is compared with that of a conventional Kalman filter to demonstrate robustness and disturbance decoupling characteristics. Aeroelastic instability may occur when an elastic structure is moving even in subcritical flow speed region. Simulation results using sliding mode observer are presented to control aeroelastic response of flapped wing system due to various external excitations as well as model uncertainty and sinusoidal disturbances in subcritical incompressible flow region.

센서융합에 의한 열차위치 추정방법 (Estimation of Train Position Using Sensor Fusion Technique)

  • 윤의상;박태형;윤용기;황종규;이재호
    • 한국철도학회논문집
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    • 제8권2호
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    • pp.155-160
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    • 2005
  • We propose a tram position estimation method for automatic train control system. The accurate train position should be continuously feedback to control system for safe and efficient operation of trains in railway. In this paper, we propose the sensor fusion method integrating a tachometer, a transponder, and a doppler sensor far estimation of train position. The external sensors(transponder, doppler sensor) are used to compensate for the error of internal sensor (tachometer). The Kalman filter is also applied to reduce the measurement error of the sensors. Simulation results are then presented to verify the usefulness of the proposed method.

상시진동신호를 이용한 교량의 감쇠특성 추정 (Estimation of Damping Properties of Bridge Structures under Ambient Vibration Condition)

  • 김성완;박동욱;김남식
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2008년도 춘계학술대회 논문집
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    • pp.93-100
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    • 2008
  • Recently, due to the advanced measurement techniques, long-term health monitoring systems have been frequently applied to existing bridges. It is known that damping ratios as one of dynamic properties would be an important parameter for evaluating the bridge condition. However, damping ratios may be normally varied depending on the external loading effects on bridges. In general, both the logarithmic decrement and the half-power band width method as a conventional method can be simply used for evaluating the damping ratios accurately when bridge response signals are measured under free vibration conditions. In this study, the Hilbert-Huang transform and the extended Kalman filter were applied to evaluate the damping ratio by using the bridge acceleration signals measured under ambient vibration condition. From the results under ambient vibration condition of bridges, it was examined that the damping ratios evaluated from both the Hilbert-Huang transform and the extended Kalman filter could be more reliable than those from conventional methods.

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Multi-information fusion based localization algorithm for Mars rover

  • Jiang, Xiuqiang;Li, Shuang;Tao, Ting;Wang, Bingheng
    • Advances in aircraft and spacecraft science
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    • 제1권4호
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    • pp.455-469
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    • 2014
  • High-precision autonomous localization technique is essential for future Mars rovers. This paper addresses an innovative integrated localization algorithm using a multiple information fusion approach. Firstly, the output of IMU is employed to construct the two-dimensional (2-D) dynamics equation of Mars rover. Secondly, radio beacon measurement and terrain image matching are considered as external measurements and included into the navigation filter to correct the inertial basis and drift. Then, extended Kalman filtering (EKF) algorithm is designed to estimate the position state of Mars rovers and suppress the measurement noise. Finally, the localization algorithm proposed in this paper is validated by computer simulation with different parameter sets.

부정 내적 공간에서의 $H^\infty$필터의 일반화를 통한 분산 $H^\infty$상태 추정기의 설계 (Design of decentralized $H^\infty$ state estimator using the generalization of $H^\infty$ filter in indefinite inner product spaces)

  • 김경근;진승희;최윤호;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.1464-1468
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    • 1997
  • We propose a decentralized state estimation method in the multisensor state estimation problem. The proposed method bounds teh maximum energy gain from uknown external disturbances to the estimation errors in the suboptimal case. And we formulate aternative H/sip .inf./ filter gain equatiions with teh idea that the suboptimal H.$^{\infty}$ filter is the special form of Kalman filter filter whose state equations are defined in indefinite inner product spaces. Using alternative filter gain equations we design the decentralized $H^{\infty}$ state estimator which is composed of local filters and central fusion filter that are suboptimal in the $H^{\infty}$ sense. In addition, the proposed update equations between global and local data can reduce unnecessary calculation burden efficently.y.

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Wind load estimation of super-tall buildings based on response data

  • Zhi, Lun-hai;Chen, Bo;Fang, Ming-xin
    • Structural Engineering and Mechanics
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    • 제56권4호
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    • pp.625-648
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    • 2015
  • Modern super-tall buildings are more sensitive to strong winds. The evaluation of wind loads for the design of these buildings is of primary importance. A direct monitoring of wind forces acting on super-tall structures is quite difficult to be realized. Indirect measurements interpreted by inverse techniques are therefore favourable since dynamic response measurements are easier to be carried out. To this end, a Kalman filtering based inverse approach is developed in this study so as to estimate the wind loads on super-tall buildings based on limited structural responses. The optimum solution of Kalman filter gain by solving the Riccati equation is used to update the identification accuracy of external loads. The feasibility of the developed estimation method is investigated through the wind tunnel test of a typical super-tall building by using a Synchronous Multi-Pressure Scanning System. The effects of crucial factors such as the type of wind-induced response, the covariance matrix of noise, errors of structural modal parameters and levels of noise involved in the measurements on the wind load estimations are examined through detailed parametric study. The effects of the number of vibration modes on the identification quality are studied and discussed in detail. The made observations indicate that the proposed inverse approach is an effective tool for predicting the wind loads on super-tall buildings.

부정 내적 공간에서의$H^\infty$ 필터의 일반화를 통한 분산 $H^\infty$ 필터의 설계 (Design of Decentralized $H^\infty$ Filter using the Generalization of $H^\infty$ Filter in Indefinite Inner Product Spaces)

  • 김경근;진승희;윤태성;박진배
    • 대한전기학회논문지:전력기술부문A
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    • 제48권6호
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    • pp.735-746
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    • 1999
  • We design the robust and inherently fault tolerant decetralized$$H^infty$$ filter for the multisensor state estimation problem when there are insufficient priori informations on the statistical properties of external disturbances. For developing the proposed algorithm, an alternative form of suboptimal$$H^infty$$ filter equations are formulated by applying an alternative form of Kalman filter equations to the indefinite inner product space state model of suboptimal$$H^infty$$ filtering problems. The decentralized$$H^infty$$ filter that consists of local and central fusion filters can be designed effciently using the proposed alternative$$H^infty$$ filiter gain equations. The proposed decentralized$$H^infty$$ filter is robust against un-known external disturbances since it bounds the maximum energy gain from the external disturbances to the estimation errors under the prescribed level$$r^2$$ in both local and central fusion filters and is also fault tolerant due to its inherent redundancy. In addition, the central fusion equations between the global and local data can reduce the unnecessary calculation burden effectively. Computer simulations are made to ceritfy the robustness and fault tolerance of the proposed algorithm.

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모바일 로봇 자세 안정화를 위한 칼만 필터 기반 센서 퓨전 (Kalman Filter-based Sensor Fusion for Posture Stabilization of a Mobile Robot)

  • 장태호;김영식;경민영;이현빈;윤동환
    • 대한기계학회논문집A
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    • 제40권8호
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    • pp.703-710
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    • 2016
  • 로보틱스 연구에서, 모바일 로봇의 모션 제어를 위해서는 로봇의 실제 위치를 정확히 추정하는 것이 중요하다. 이를 위해 본 연구에서는, 두 개의 서로 다른 센서 데이터를 칼만필터로 융합하여 로봇의 위치인식을 개선하는 연구를 진행한다. 칼만필터로 융합한 두 개의 센서 측정값은 카메라 영상으로부터 측정된 모바일 로봇의 전역(global) 위치 좌표(x, y)값과 모바일 로봇 바퀴에 부착된 엔코더로부터 측정된 로봇의 직선 및 각속도 값이다. 다음으로 칼만필터로부터 계산된 모바일 로봇의 위치값을 모바일 로봇의 자세 안정화에 피드백하여 모션 제어의 퍼포먼스를 향상시켰다. 최종적으로 논문에서 제안한 센서융합 위치인식 기술과 모션제어기를 실제 로봇에 적용하여 실험적으로 검증하였다. 또한 모션제어에 단일 센서를 피드백으로 사용한 경우와 칼만필터로 융합한 위치 값을 사용한 경우를 비교하므로 칼만필터 기반 센서 융합 기술을 사용한 경우의 퍼포먼스 향상을 확인하였다.