Computing quasi-LTI robustness margins in sampled-data systems

The robustness test for sampled-data systems with slowly time-varying pertu rbations is known to be infinite dimensional in nature. This note develops computationally explicit upper and lower bounds for the corresponding stabi lity radius, presenting them in terms of linear matrix inequalities (LMIs) gi,en by state-space formulas derived. The upper bound is shown to converge monotonically to the stability radius, and so can be systematically tighte ned at the cost of increased computational effort. The loa er bound is mono tonically increasing, and is conjectured to also converge to the stability radius.