Probabilistic ultimate bounds and invariant sets in nonlinear systems

Abstract

This article extends the notions of probabilistic ultimate bounds (PUB) and probabilistic invariant sets (PIS) to nonlinear continuous-time systems providing tools for their characterization and for the usage of these concepts in control design. Two design strategies are proposed that allow finding a nonlinear control law which ensures that the closed loop system is probabilistically ultimate bounded to a desired region. These strategies are based on Lyapunov and stochastic feedback linearization, respectively.