Decentralized adaptive control of large-scale stochastic nonlinear systems in parametric non-strict-feedback forms

In this paper, decentralized adaptive control problem is studied for a class of stochastic nonlinear large-scale systems in parametric non-strict-feedback forms. By employing the stochastic Lyapunov-like theorem and the backstepping design technique, the adaptive state feedback decentralized controller and parameters adaptive law are developed. It is shown that such an adaptive control scheme can guarantee that the closed-loop, large-scale, interconnected stochastic nonlinear system is globally bounded stable in probability.