Interval predictors for a class of uncertain discrete-time systems - Meslem Nacim (Acta cybernetica, 2020)
This work presents set-valued algorithms to compute tight interval predictions of the state trajectories for a class of uncertain dynamical systems, where the dynamics is described as a sum of a linear and a nonlinear term. Based on interval analysis and the analytic expression of the state response of discrete-time linear systems, non-conservative numerical schemes are proposed. Moreover, under some stability conditions, the convergence of the width of the predicted state enclosures is proved. The performance of the proposed set-valued algorithms is illustrated through two numerical examples, and the results are compared to that obtained with another method selected from the literature.