一类非线性动态系统的一致性分散可靠性预测

针对一类带有隐含退化过程的非线性动态系统,提出了一种基于粒子滤波的一致性分散可靠性预测方法。该方法将原系统重叠分解为若干个相互关联的子系统,每个子系统利用其局部测量信息以及子系统间通信得到的信息,估计出原系统的状态和参数,进而预测原系统的可靠性。同时,该方法通过一致性策略使得所有子系统的估计和预测结果保持一致。五容水箱模型的仿真实验结果表明,该方法能够很好地预测系统的可靠性,同时该方法能够使得所有子系统的估计和预测结果保持一致。

Consensus-based decentralized reliability prediction for nonlinear dynamic system

A consensus-based decentralized reliability prediction method based on particle filtering is proposed for a nonlinear dynamic system with hidden degradation process.The degradation process is hidden means that the degradation cannot be measured directly.In this method，the original system is divided into several interconnected subsystems with overlapping decompositions，and then using the particle filtering algorithm at each subsystem，the states and parameters of the original system are estimated by each subsystem with the information of local measurements and the communications between subsystems，subsequently reliability of original system can also be predicted.Simultaneously，the method makes consensus-based estimation and prediction results for all subsystems with consensus strategy.Finally，from simulation experiments of a five-tank vessels model the degradation of system reliability can be predicted well，as well as the estimation and prediction results of all subsystems can be consensus.