Adaptive partial-state feedback control for stochastic high-order nonlinear systems with stochastic input-to-state stable inverse dynamics

This paper aims to solve the adaptive stabilization problem for a class of stochastic high-order nonlinear systems with stochastic inverse dynamics and nonlinear parameterization. Under the weaker assumptions on stochastic inverse dynamic and nonlinear functions, by generalizing the adding a power integrator technique, using the idea of changing supply function and parameter separation technique, a smooth adaptive partial-state feedback controller is constructed to render the closed-loop system globally stable in probability and all states can be regulated to the origin almost surely. The effectiveness of the designed controller is demonstrated by a simulation example.