We consider a general uncertain nonlinear dynamical system defined in a certain model set, and reformulate a problem of robustness bifurcation analysis (RBA), which has been originally formulated in our previous work. As such, we develop an efficient computational method for the RBA, which can be used for quantitative evaluation of bifurcation robustness in uncertain dynamical systems. Specifically, we first linearize the uncertain system properly and then apply a feedback transformation technique to reduce the RBA problem to a linear robustness analysis one, which can be solved using μ-analysis, a common analysis technique in robust control theory. Finally, we provide robustness analysis of a gene regulatory network model where oscillatory behavior appears according to Hopf bifurcation. We give quantitative evaluation of the bifurcation robustness using the RBA method proposed here.
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