A Modelling and Analysis Tool for Systems with Probabilistic Behavior: Probabilistic Continuous Petri Net

So far, Continuous Petri nets (CPNs) have been a useful tool not only for approximating discrete-event system but also for modeling continuous processes. In applications there exist many continuous dynamic systems which have to deal with probabilistic behavior. However many CPNs as described in the literature are not able to model probabilistic continuous systems. In this paper, the CPN is augmented with firing probability, and a noel continuous Petri net, i.e., the probabilistic continuous Petri nets (PCPNs) is defined. The enabling and firing semantics of transitions of the PCPN are investigated, and the calculation of IFSs and its firing probability are developed. Some polices and algorithms to undertake PCPN behavioral analysis are proposed. Also, a chemical process is illustrated.