Robust control with variance finite-signal-to-noise models

The newly introduced finite signal-to-noise (FSN) models can model two kinds of uncertainties in controlled linear systems: the so-called finite-signal-to-noise ratio and multiplicative noises. FSN models uncertainties as white noises of intensity depending affinely on some signal variances in the controlled systems. This paper provides a complete solution for the analysis and synthesis of the linear system with FSN model uncertainty. The linear variance operator is a key mechanism used to deduce results for stability and performance robust to these uncertainties.