Stability and bifurcation analysis of systems described by nonexact models

In this paper, we propose a procedure to perform stability and bifurcation analysis in case of model and parameters uncertainty. Monte Carlo methods are used to compute the sensitivity of the Hopf bifurcation locus and to detect the most probable stability regions. In this way, it is possible to quantify the effects of uncertainty on the predictions without a great amount of calculations. Advantages, in case of models describing real processes and systems, are in terms of reliability, good design, and safety.