This paper considers global asymptotic stabilization in probability for a class of cascaded stochastic nonlinear systems. The uncertainties do not meet the general matched conditions, and only boundedness of the uncertainties is assumed. Drawing on the stochastic asymptotic stability theorem, a novel robust controller is constructed based on the state transformation technique and the gradient method, which ensures that the closed-loop systems are globally asymptotically stable in probability. A numerical example is given to illustrate the effectiveness of the result.
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