General Stochastic Convergence Theorem and Stochastic Adaptive Output-Feedback Controller

摘要: This paper is devoted to the analysis methods/tools stochastic convergence and adaptive output-feedback control. As first contribution, a general theorem proposed for nonlinear systems. The doesn't necessarily involve positive-definite function of system states with negative-semidefinite infinitesimal, essentially different from LaSalle's (see e.g., [1] ), hence can provide more opportunities achieve convergence. Moreover, as direct extension theorem, version Barb ă lat's lemma obtained, which requires concerned process be almost surely integrable, rather than absolutely integrable in sense expectation, unlike [2] . second supported by an control strategy established global stabilization class systems severe parametric uncertainties coupled unmeasurable states. Its feasibility takes substantial effort, largely based on theorem. Particularly, resulting closed-loop system, certain boundedness integrability are shown celebrated nonnegative semimartingale furthermore, desired achieved via