Decentralized robust adaptive output feedback control of stochastic nonlinear interconnected systems with dynamic interactions

For a class of stochastic nonlinear large-scale systems with output dynamic interactions, the problem of robust adaptive control is researched in this paper. Under the assumptions that the inverse dynamics of the subsystems are stochastic input-to-state stable, a decentralized robust adaptive output feedback controller is designed by combining the backstepping method and changing supply functions technique. Under some milder conditions, it is shown that the outputs can be regulated into an arbitrarily small neighborhood of the origin in probability and the other signals in the closed-loop system are globally bounded in probability by tuning design parameters. Moreover, when the drift and diffusion terms vanish at the origin, the equilibrium of the closed-loop system is globally stable in probability and the outputs tend to the origin almost surely. A simulation example is presented to demonstrate the effectiveness of the designed controller.