Hybrid System State Tracking and Fault Detection Using Particle Filters

When particle filters are used for fault detection, they have the problem of sample impoverishment, which means there are not enough particles that can transition to a rare-occurring faulty mode. The consequence is that the fault cannot be properly detected. This paper proposes a method to overcome this problem. Essentially, we develop an algorithm for tracking the states of hybrid systems where fault detection is modeled as a special case of the state tracking of a hybrid system. Extensive simulations are carried out to analyze the effects of various parameters on the performance of the algorithm. It is shown that our algorithm can detect both known and unknown faults using a very small number of particles