Sufficient conditions for the analysis of stability of linear systems with polytopic uncertainties are presented in this paper. The robust stability is guaranteed by the existence of a parameter dependent Lypaunov function obtained from the feasibility test of a set of linear matrix inequalities (LMIs) formulated at the vertices of the uncertainty polytope. Three conditions are presented, and the results are also compared with the analysis based on quadratic stability (same Lyapunov function for the entire set of uncertainties), for continuous as well as discrete-time systems. The first condition exploits the use of some extra variables (matrices) in the LMIs, and the second one uses a larger number of LMIs. These two conditions have recently appeared in the literature and are less conservative than quadratic stability. The third condition, proposed in this paper, combines the two ideas, yielding better results, and contains the previous conditions as particular cases. Several examples are presented to illustrate the numerical performance of the LMI conditions in terms of efficiency and computational complexity.
Robust stability; parameter dependent Lyapunov function; linear matrix inequality; polytopic uncertainty
