Further results on global adaptive stabilisation for a class of uncertain stochastic nonlinear systems.

This paper considers the global adaptive stabilisation for a class of uncertain stochastic nonlinear systems. Comparing with the existing relevant literature, the systems under investigation allow more serious unknowns/uncertainties. More importantly, by remarkably reducing the dimension of dynamic compensator for system unknowns (fromnto 2) and considerably diminishing the overparametrisation in the existing literature, this paper proposes an improved design scheme for adaptive state-feedback controllers. It is turned out that, with the designed controller in loop, all the closed-loop system states are globally bounded and the original system states converge to the origin, both in the sense of probability one. A simulation example is also given to demonstrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]