Title :
Robust stability of polytopic systems via polynomially parameter-dependent Lyapunov functions
Author :
Chesi, G. ; Garulli, A. ; Tesi, A. ; Vicino, A.
Author_Institution :
Dipt. di Ingegneria dell´´Inf., Siena Univ., Italy
Abstract :
In this paper robust stability of state space models with respect to real parametric uncertainty is considered. Specifically, a new class of parameter-dependent quadratic Lyapunov functions for establishing stability of a polytope of matrices is introduced, i.e., the Homogeneous Polynomially Parameter-Dependent Quadratic Lyapunov Functions (HPD-QLFs). The choice of this class, which contains parameter-dependent quadratic Lyapunov functions whose dependence on the uncertain parameters is expressed as a polynomial homogeneous form, is motivated by the property that a polytope of matrices is stable if and only there exists a HPD-QLF. The main result of the paper is a sufficient condition for determining the sought HPD-QLF, which amounts to solving linear matrix inequalities (LMIs) derived via the complete square matricial representation (CSMR) of homogeneous matricial forms and the Lyapunov matrix equation. Numerical examples are provided to demonstrate the effectiveness of the proposed approach.
Keywords :
Lyapunov matrix equations; linear matrix inequalities; linear systems; parameter space methods; stability; state-space methods; uncertain systems; LMI; Lyapunov matrix equation; complete square matricial representation; homogeneous matricial form; linear matrix inequalities; linear systems; parameter dependent quadratic Lyapunov function; parametric uncertainty; polytopic systems; robust stability; stability; state space models; sufficient condition; Computational complexity; Equations; Linear matrix inequalities; Lyapunov method; Polynomials; Robust stability; Stability criteria; State-space methods; Sufficient conditions; Uncertainty;
Conference_Titel :
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
Print_ISBN :
0-7803-7924-1
DOI :
10.1109/CDC.2003.1272307