Particle Filtering Algorithm for Fault Diagnosis of Multiple Model Hybrid Systems with Incomplete Models
不完备多模型混合系统故障诊断的粒子滤波算法

A particle filtering algorithm is presented for fault diagnosis of hybrid dynamic systems with incomplete models.Un-modeled dynamics of complex systems is denoted as"unknown-fault".Firstly,the divergence of general particle filter(GPF)for imperfect systems is discussed.Secondly,two kinds of statistics are put forward,i.e.,normalization factor of particles(W),and belief of maximal a-posteriori probability estimation state(B).Thirdly,threshold logic is presented to detect unknown-faults,and its correctness is proved under some reasonable assumptions.The efficiency of the method is testified by the simulated results.