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Satellite fault diagnosis method based on predictive filter and empirical mode decomposition

Journal of Systems Engineering and Electronics 2011年第1期22卷 83-87页

作者： Yi Shen Yingchun Zhang Zhenhua Wang School of Astronautics Harbin Institute of Technology Harbin 150001 E R. China

A novel satellite fault diagnosis scheme is presented based on the predictive filter and empirical mode composition（EMD）.First,the predictive filter is utilized to obtain the fault estimation,which is corrupted by *** the EMD method is introduced to decompose the fault estimation into a finite number of intrinsic mode functions and extract the trend of faults for fault *** proposed scheme has the ability of diagnosing both abrupt and incipient faults of the actuator in a satellite attitude control subsystem.A mathematical simulation is given to illustrate the effectiveness of the proposed scheme.

关键词： satellite fault diagnosis predictive filter empirical mode decomposition(EMD).

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Stochastic stability of cubature predictive filter

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Science China(Information Sciences) 2016年第9期59卷 107-130页

作者： Lu CAO Xiaoqian CHEN The State Key Laboratory of Astronautic Dynamics China Xi'an Satellite Control Center College of Aerospace Science and Engineering National University of Defense Technology

In this paper, the cubature predictive filter(CPF) is derived based on a third-degree spherical-radial cubature rule. It provides a set of cubature-points scaling linearly with the state-vector dimension, which makes it possible to numerically compute multivariate moment integrals encountered in the nonlinear predictive filter(PF). In order to facilitate the new method, the algorithm CPF is given firstly. Then, the theoretical analyses demonstrate that the estimated accuracy of the model error and system for the proposed CPF is higher than that of the traditional PF. Moreover, the authors analyze the stochastic boundedness and the error behavior of CPF for general nonlinear systems in a stochastic framework. In particular, the theoretical results present that the estimation error remains bounded and the covariance keeps stable if the system’s initial estimation error,disturbing noise terms as well as the model error are small enough, which is the core part of the CPF *** of the results have been demonstrated by numerical simulations for a nonlinear example system.

关键词： predictive filter cubature rule nonlinear filter stochastic system

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predictive filter for Estimating the Target Acceleration

Predictive Filter for Estimating the Target Acceleration

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第32届中国控制与决策会议

作者： LI Rui LIU Ying ZHANG Jin LIANG Xiao-xi WEI Ya-li Shanghai Electro-Mechanical Engineering Institute

In this paper,in the background of studying the terminal guidance of an air-to-air missile,a real time predictive filter is derived for target acceleration estimation without the utilization of angular measurements from gyros,which will reduce the overload and the miss distance of missiles attacking maneuverable *** compare to Kalman filter,the result of simulation shows this algorithm has more accuracy,availability and robustness.

关键词： predictive filter Kalman filter Target Acceleration

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Initial alignment of Inertial Navigation System based on a predictive iterated Kalman filter

Initial alignment of Inertial Navigation System based on a p...

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第37届中国控制会议

作者： Guanghao CHENG Songyin CAO Lei GUO Wenhua CHEN Department of Automation College of Information EngineeringYangzhou University National Key Laboratory on Aircraft Control Technology School of Instrumentation Science and Opto-Electronics EngineeringBeihang University Department of Aeronautical and Automotive Engineering Loughborough University

Inertial navigation systems（INSs） are widely used in practical applications. This paper considers the problem of initial alignment for an inertial navigation system. As the modeling error of an INS is difficult to be measured accurately, it will decrease the accuracy of the initial alignment. In this paper, a predictive iterated Kalman filter（PIKF） is proposed for a class of INSs with the modeling error and Gaussian noise. Firstly, the modeling error is estimated by a predictive filter. Then, in order to reduce the error between the one step prediction of Kalman filter and the true value, a new filtering method combining a predictive filter with an iterative Kalman filter is used to improve the alignment accuracy. Finally, simulations for the stationary alignment of an INS are given to show the efficiency of the proposed approach.

关键词： Inertial Navigation System Initial alignment predictive filter Kalman filter Iterative filter

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