Decentralized adaptive tracking of stochastic nonlinear interconnected systems by output feedback

This paper studies the tracking problem for a class of stochastic nonlinear interconnected systems with unknown parameters involved. By employing filtered transformation, the stochastic Lyapunov-like theorem and the backstepping design technique, a decentralized output-feedback controller and parameter adaptive law are proposed. It is proved that the designed adaptive controllers can ensure the boundedness in probability for all the signals in the closed-loop system. The tracking error can converge to a small residual set around the origin in the sense of mean quartic value.