This paper deals with the problem of H∞ output feedback control for uncertain stochastic systems with time-varying delays. The parameter uncertainties are assumed to be time-varying norm-bounded. The aim is the design of a full-order dynamic output feedback controller ensuring robust exponential mean-square stability and a prescribed H∞ performance level for the resulting closed-loop system, irrespective of the uncertainties. A sufficient condition for the existence of such an output feedback controller is obtained and the expression of desired controllers is given

This paper considers the problem of robust H∞ filtering for uncertain two-dimensional (2-D) continuous systems described by the Roesser state-space model. The parameter uncertainties are assumed to be norm-bounded in both the state and measurement equations. The purpose is the design of a 2-D continuous filter such that for all admissible uncertainties, the error system is asymptotically stable, and the H∞ norm of the transfer function, from the noise signal to the estimation error, is below a prespecified level. A sufficient condition for the existence of such filters is obtained in terms of a set of linear matrix inequalities (LMIs). When these LMIs are feasible, an explicit expression of a desired H∞ filter is given. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed method

This note provides an improved asymptotic stability condition for time-delay systems in terms of a strict linear matrix inequality.Unlike previous methods, the mathematical development avoids bounding certain cross terms which often leads to conservatism. When time-varying norm-bounded uncertainties appear in a delay system, an improved robust delay-dependent stability condition is also given. Examples are provided to demonstrate the reduced conservatism of the proposed conditions.

This note considers the problem of robust H∞ filtering for uncertain Markovian jump linear systems with time-delays which are timevarying and depend on the system mode. The parameter uncertainties are time-varying norm-bounded. The aim of this problem is to design a Markovian jump linear filter that ensures robust exponential mean-square stability of the filtering error system and a prescribed L2-induced gain from the noise signals to the estimation error, for all admissible uncertainties. A sufficient condition for the solvability of this problem is obtained. The desired filter can be constructed by solving a set of linear matrix inequalities. An illustrative numerical example is provided to demonstrate the effectiveness of the proposed approach.

This paper is concerned with the problem of robust H∞ filtering for linear systems with both discrete and distributed delays, which are subject to norm-bounded time-varying parameter uncertainties. Both the state and measurement equations are assumed to have discrete and distributed delays. A delay-dependent condition for the existence of H∞ filters is proposed, which is less conservative than existing ones in the literature. Via solutions to certain linear matrix inequalities, general full-order filters are designed that ensure asymptotic stability and a prescribed H∞ performance level, irrespective of the parameter uncertainties. An illustrative example is provided to demonstrate the effectiveness and the reduced conservatism of the proposed method.