Semiglobal exponential input-to-state stability of sampled-data systems based on approximate discrete-time models

Several control design strategies for sampled-data systems are based on a discrete-time model. In general, the exact discrete-time model of a nonlinear system is difficult or impossible to obtain, and hence approximate discrete-time models may be employed. Most existing results provide conditions under which the stability of the approximate discrete-time model in closed-loop carries over to the stability of the (unknown) exact discrete-time model but only in a practical sense, meaning that trajectories of the closed-loop system are ensured to converge to a bounded region whose size can be made as small as desired by limiting the maximum sampling period. In addition, some sufficient conditions exist that ensure global exponential stability of an exact model based on an approximate model. However, these conditions may be rather stringent due to the global nature of the result. In this context, our main contribution consists in providing rather mild conditions to ensure semiglobal exponential input-to-state stability of the exact model via an approximate model. The enabling condition, which we name the Robust Equilibrium-Preserving Consistency (REPC) property, is obtained by transforming a previously existing consistency condition into a semiglobal and perturbation-admitting condition. As a second contribution, we show that every explicit and consistent Runge-Kutta model satisfies the REPC condition and hence control design based on such a Runge-Kutta model can be used to ensure semiglobal exponential input-to-state stability of the exact discrete-time model in closed loop.Comment: 10 page

On stability of sets for sampled-data nonlinear inclusions via their approximate discrete-time models and summability criteria

International audienceThis paper consists of two main parts. In the first part, we provide a framework for stabilization of arbitrary (not necessarily compact) closed sets for sampled-data nonlinear differential inclusions via their approximate discrete-time models. We generalize [19, Theorem 1] in several different directions: we consider stabilization of arbitrary closed sets, plants described as sampleddata differential inclusions and arbitrary dynamic controllers in the form of difference inclusions. Our result does not require the knowledge of a Lyapunov function for the approximate model, which is a standing assumption in [21] and [19, Theorem 2]. We present checkable conditions that one can use to conclude semi-global asymptotic (SPA) stability, or global exponential stability (GES), of the sampled-data system via appropriate properties of its approximate discrete-time model