Parallel event-triggered dynamic output feedback control for nonlinear networked systems with randomly occurring multiple communication delays

This paper investigates the issue of parallel event-triggered (PET) dynamic output feedback control for networked control systems (NCSs) built by the discrete-time T–S fuzzy model. Initially, a novel PET dynamic output feedback controller is designed. Based on saving network resources and enhancing transmission efficiency, the PET strategy makes full use of relative and absolute triggering condition information. And the dynamic output feedback control can not only address unmeasurable states but also provide a better response to the internal information of the system. The random multiple communication delays and the $\ell$th-order Rice fading model with different channel coefficients, meanwhile, are both applied in the system. It is closer to the actual situation. Subsequently, new sufficient conditions of membership function dependence are proposed via the staircase function approximation method combined with Lyapunov stability. It guarantees that the system is exponentially mean square stable (EMSS) with $H_{\infty }$ performance. Ultimately, the presented results are validated using two examples. In the future, we will explore the correlative research of T–S fuzzy Markov jump NCSs.