Dynamic Periodic Event-Triggered Adaptive Prescribed Performance Control of Uncertain Semi-Strict Feedback Systems With Application

This paper investigates the event-based adaptive global prescribed performance control (PPC) for a class of uncertain semi-strict feedback nonlinear systems with application to the networked spacecraft simulator (NSS) system. First, to reduce the communication frequency, a novel dynamic periodic event-triggering mechanism (DPETM) is proposed. It can not only avoid continuously monitoring the event-triggering conditions and the Zeno phenomenon in mechanism, but also reduce the trigger frequency on the premise of maintaining the closed-loop system performance. Then, an event-based adaptive global prescribed performance controller is designed by using the backstepping methodology and adopting the time-varying scaling transformation and the nonlinear transformation. The proposed method can ensure that all signals of the resulted closed-loop system remain bounded, meanwhile, the tracking error is always within the predetermined range for any initial values. Finally, the effectiveness, the engineering feasibility and the advantages of the proposed control method are demonstrated by utilizing an NSS system.