State feedback control of linear systems in the presence of devices with finite signal-to-noise ratio

This paper provides necessary and sufficient conditions for mean-square state-feedback stabilization of linear systems whose white noise sources have intensities affinely related to the variance of the signal they corrupt. Systems with such noise sources have been called finite signal-to-noise (FSN) models, and the stability results provided in prior work were only sufficient conditions. The upper bounded L₂ performance is also guaranteed herein by solving a control problem which is nonconvex only due to a certain scaling parameter. By fixing this parameter convex programming algorithms provide the control of FSN models of linear systems