Valter J. S. Leite

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A sufficient condition for robustD-stability of linear systems with polytope type uncertainties is proposed. The result is based on a linear parameter-dependent Lyapunov function obtained from the feasibility test of a set of linear matrix inequalities (LMIs) defined at the vertices of the polytope. This improved LMI condition encompasses previous results(More)
International Journal of Control Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t713393989 Improved robust H∞ control for neutral systems via discretised Lyapunov-Krasovskii functional Fernando O. Souza a; Reinaldo M. Palhares a; Valter J. S. Leite b a Department of(More)
We present a methodology for computing output feedback control laws for a class of nonlinear systems subject to input saturations. This class of systems consists of a L'ure type nonlinear system with some time-varying parameters which are assumed to be real-time available. Based on some tools from the absolute stability theory, on a modified sector(More)
Sufficient linear matrix inequality LMI conditions to verify the robust stability and to design robust state feedback gains for the class of linear discrete-time systems with time-varying delay and polytopic uncertainties are presented. The conditions are obtained through parameter-dependent Lyapunov-Krasovskii functionals and use some extra variables,(More)
This paper presents less conservative LMIs conditions for robust stability analysis and for robust controller design of uncertain discrete-time systems with time-varying delay in the state vector. The uncertainty, supposed to be described in the polytopic framework, affects all matrices of the system. The proposed conditions are convex and delay dependent.(More)
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.(More)