Two stochastic filters and their interval extensions

In this paper, two well-known stochastic filtering algorithms, Kalman and particle filters, are presented. Their extensions using interval analysis are described. A fuel cell system case study is considered together with specific scenarios representing situations in which interval filters are relevant. The results confirm the advantage of the interval filters in such situations.