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状态—参数联合估计方法及其在液体火箭发动机健康监控中的应用
引用本文:吴建军,张育林,陈启智.状态—参数联合估计方法及其在液体火箭发动机健康监控中的应用[J].国防科技大学学报,1997,19(4):14-20.
作者姓名:吴建军  张育林  陈启智
作者单位:国防科技大学航天技术系
基金项目:校实验研究基金资助项目
摘    要:基于传统的扩展卡尔曼滤波器(EKF),本文提出了一种带次优渐消因子的EKF用于非线性时变随机动态系统状态与参数的联合估计。应用于液体火箭发动机健康监控算法的仿真研究表明,本文所提出的联合估计器具有较好的收敛性、实时性和动态跟踪能力。此外,文中还讨论了联合估计器应用于实际系统的有关问题。

关 键 词:液体推进剂火箭发动机,故障诊断,故障隔离,状态估计,参数估计,非线性动态系统
收稿时间:1997/4/20 0:00:00

The Joint Estimation Approach of States and Parameters for Liquid Rocket Engine Health Monitoring
Wu Jianjun,Zhang Yulin and Chen Qizhi.The Joint Estimation Approach of States and Parameters for Liquid Rocket Engine Health Monitoring[J].Journal of National University of Defense Technology,1997,19(4):14-20.
Authors:Wu Jianjun  Zhang Yulin and Chen Qizhi
Institution:Department of Aerospace Technology, NUDT, Changsha, 410073;Department of Aerospace Technology, NUDT, Changsha, 410073;Department of Aerospace Technology, NUDT, Changsha, 410073
Abstract:Based on a coventional Extended Kalman Filter (EKF), a sub-optimal fading factor EKF is proposed in this paper, which can be used for the joint estimation of states and parameters of nonlinear time-varying stochastic systems. It is used for health monitoring in such a complex system as liquid rocket engine. Numerical simulation result shows the proposed estimator has better properties such as convergence, real time, and dynamic tracking ability etc. . In addition, some problems connected with the joint estimation and the applicability for real plants are also discussed.
Keywords:liquid propellant rocket engine  fault diagnosis  fault isolation  state estimation  parameter estimation  nonlinear dynamic system  
本文献已被 CNKI 等数据库收录!
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