Stabilization of nonlinear plants with sampled information

This paper considers the problem of driving to 0 by means of state feedback the state of a nonlinear, time-invariant plant, when only an approximate model of the plant is known and the information about its state is available, for control purposes, only at equally spaced sampling instants. To this aim, a specific model-based control scheme, which includes an observer, is used and suitable hypotheses of Lipschitz type about the plant dynamics and the error between the model and the plant are considered. The main results consist of sufficient conditions on the length of the sampling interval that assure the achievement of the desired control objective. The present results improve previous ones, found in the networked systems literature or due to the authors, by extending their applicability to general nonlinear plants in a broad range of situations.