Adaptive state feedback control of output-constrained stochastic nonlinear systems with stochastic integral input-to-state stability inverse dynamics

This article studies the adaptive state-feedback control problem of output-constrained stochastic high-order nonlinear systems with stochastic integral input-to-state stability (SiISS) inverse dynamics. A key nonlinear transformation function is constructed to convert the original output-constrained stochastic nonlinear system into an equivalent form without any output constraint. By subtly using the SiISS small-gain condition and fully extracting the characteristics of system nonlinearities, two new control design and analysis methods are developed to guarantee that the closed-loop system has an almost surely unique solution, all the closed-loop signals are bounded almost surely, and the equilibrium point is stable in probability without the violation of output constraint. A simulation result is provided to show the effectiveness of this control method.

Automated summary

This article investigates the adaptive state-feedback control problem of output-constrained stochastic high-order nonlinear systems with stochastic integral input-to-state stability (SiISS) inverse dynamics. Two new control design and analysis methods are proposed based on a key nonlinear transformation function and the use of SiISS small-gain condition. The simulation result demonstrates the effectiveness of this control method in guaranteeing system stability without violating output constraint.