Adaptive state-feedback stabilization of stochastic high-order nonholonomic systems with nonlinear parameterization

This paper investigates the adaptive stabilization of stochastic high-order nonholonomic systems with nonlinear parameterization. An adaptive state feedback controller is designed by using the parameter separation technique and input-state scaling technique, and adding a power integrator backstepping approach. The switching strategy is proposed to eliminate the phenomenon of uncontrollability and to guarantees that the closed-loop system has an almost surely unique solution for any initial state, the equilibrium of interest is globally stable in probability, and the state can almost surely be regulated to the origin. Simulation examples demonstrate the effectiveness of the proposed scheme.