Anti-disturbance Control Based On Uncertain Data.

In this paper, we describe a novel method for constructing probabilistic robust disturbance rejection control for systems contain uncertain data in which a scenario optimization method is used to deal with the nonlinear and unbounded uncertainties. For anti-disturbance, a reduced order disturbance observer is considered and a state-feedback controller is designed. Sufficient conditions are presented to ensure that the resulting closed-loop system is stable and a prescribed H∞ performance index is satisfied. A numerical example is presented to illustrate the effectiveness of the techniques proposed and analyzed.