Reliability analysis of dynamic systems based on stochastic reachability

The reliability analysis of systems may be very time-consuming by traditional sampling algorithms such as Monte Carlo especially for dynamic systems, because the states of dynamic systems are time-dependent. We address this main problem of dynamic systems with a new reliability analysis method based on stochastic reachability which has been studied in the field of control theory and control engineering. Randomness in dynamic systems will be described by this approach. It is involved from the following two aspects. One is to use jumps involving probability distributions when settling the time automata model. This adds the possibility to represent component failures. Another aspect is to put stochastic differential equation components inside the dynamic system models. By doing that, the impact of external disturbances such as environmental temperature can be taken into consideration.