Observer-Based Periodic Event-Triggered Adaptive Fuzzy Control for Networked Nonlinear Systems

This article addresses the periodic event-triggered adaptive output feedback control problem for networked system with unknown nonlinear dynamics. Based on the output-dependent periodic event-triggered mechanism (PETM), a nonlinear observer is designed to estimate system states, where the fuzzy-logic systems-based approximation method and adaptive technique are employed to approximate and compensate for uncertainties. To enhance resource utilization efficiency in communication channels, a new observer and parameter estimators-dependent parallel PETM is proposed to schedule intermittent packet transmission. Then, a digital controller is designed to reduce frequent control updating. By constructing novel piecewise Lyapunov functional, it is proven that the underlying system states, the observation error signals and parameter estimation signals are semiglobally uniformly ultimately bounded. In addition, the proposed control method is applied to solve the stabilization problem of networked interconnected systems. Finally, a numerical simulation is performed to show the efficiency of the developed control method.