This paper focuses on state-feedback adaptive control for stochastic low-order nonlinear systems with an output constraint and stochastic integral input-to-state stability (SiISS) inverse dynamics. The system with an output constraint was transformed straightforwardly into the equivalent system without a constraint using important coordinate transformations. SiISS was used to characterize unmeasured stochastic inverse dynamics. By introducing Lyapunov functions and using the stochastic systems stability theorem, we constructed a new adaptive state-feedback controller that assures the closed-loop system's trivial solution is stable in probability while fulfilling the requirements of the output constraint and all closed-loop signals are likely to be almost surely bounded. The validity of the control scheme presented in this paper was demonstrated by using simulation outcomes.

This paper studies the global asymptotic stabilization problem of strict-feedforward nonlinear systems with state and input delays. We will first transform the considered system into an equivalent system by constructing the novel parameter-dependent state feedback controller and introducing the appropriate coordinate transformation. After that, the global asymptotic stability of the closed system is proved by giving the proper Lyapunov-Krasovskii functional and using the stability criterion of time-delay system.