摘要
研究了一类带有某种隐含的性能退化过程的动态系统的实时可靠性预测问题。在初始性能变量值不确定的情况下,首先基于粒子滤波算法和迭代极大似然估计方法,利用系统的输出信息辨识了性能退化轨道函数中的未知参数,并实时估计性能变量值。然后根据性能退化过程辨识结果实时地预测系统在未来一段时间内的可靠性指标。基于三容水箱的仿真实验结果验证了方法的有效性。
The real-time reliabihty prediction problem for a class of dynamic systems with certain kind of hidden performance degradation process is studied. Under the condition that the initial value of the performance variable is uncertain, the unknown parameters in the performance degradation path function are identified based on the output information of the system, using particle filtering and recursive maximum likelihood estimation algorithins. After estimating the performance variable in real time, the reliabihty indices of the system in the near future are predicted according to the identification results of the performance degradation process. The computer simulation based on a three-vessel water tank shows the effectiveness of the proposed method.
出处
《控制工程》
CSCD
2008年第1期85-87,共3页
Control Engineering of China
基金
国家自然科学基金资助项目(60574084)
关键词
动态系统
性能退化
可靠性
粒子滤波器
迭代极大似然估计
dynamic systems
performance degradation
reliability
particle filter
recursive maximum hkelihood estimation