부산대학교 도서관

This paper proposes dynamic updates in stochastic backstepping control for a networked system. The system is prone to network uncertainties such as packet loss and transmission delay. These uncertainties introduce stochasticity in the system. The dynamic updates and generic triggering conditions for each subsystem are formulated to ensure system stability. The neural networks are used to precisely approximate stabilizing functions and control input because each subsystem dynamics has stochastic functions. The triggering conditions are further used to obtain generic expressions for permissible value of round-trip data packet losses and delay between consecutive triggers for each subsystem. A comprehensive analysis of proposed design is done for trajectory tracking by a networked system prone to uncertainties.