A practical approach to worst-case H∞ performance computation

A practical method is proposed in this paper to compute a lower bound on the worst-case H
_∞
performance for a linear time-invariant system affected by parametric uncertainties. The problem is first solved for a few frequencies by combining a gradient computation with a hamiltonian-like method. A series of linear programming problems are then solved using the previous results as an initialization, and worst-case values of both the frequency and the uncertainties are determined. The application of the resulting algorithm to a challenging industrial problem proves conclusive and shows that high-order systems with highly repeated uncertainties can be handled: the impact of wind on passengers' comfort on board a flexible transport aircraft is indeed evaluated, and worst-case values of both the flight and the mass parameters are obtained.