Synchronization Control for T-S Fuzzy Neural Networks With Time Delay: A Novel Event-Triggered Mechanism

A novel aperiodic event-triggered control is adopted to address the synchronization issue of T-S fuzzy neural networks (FNNs) with time delay. This control strategy refers to the execution of control tasks in a control system based on real-time events, rather than following a fixed time interval. It allows for more flexible and faster responses to real-time events, and can reduce the computational load, energy consumption, and system costs. At first, a linear event-triggered control mechanism is formulated, in which its triggering condition includes an exponential term. Subsequently, LMI-based synchronization criteria are deduced under the formulated event-triggered control. Additionally, a novel approach that employs the reduction to absurdity technique is proposed to address the non-existence of Zeno behavior. Eventually, the proposed theory's efficacy is demonstrated by employing an example and an accompanying simulation.