Intelligent hybrid event-triggered synchronization control of delayed neural networks with actuator failure via semi loop functional
Xianhao Zheng, Jun Wang, Kaibo Shi, Xiao Feng Cai, Yiqian Tang · Discrete and Continuous Dynamical Systems - S · 2024
This paper investigates the synchronization problem of delayed neural networks (DNNs). First, we introduce an intelligent hybrid event-triggered scheme (IHETS) that allows sensors to wait within a specified time range after triggering measurements, thereby reducing network load and avoiding Zeno behavior. Then, a semi-looped-functional approach with relaxed constraints is adopted, which eliminates the need for strict requirements on negative definite derivatives. Moreover, we introduce a novel series of less conservative linear matrix inequalities (LMIs) to guarantee sufficient conditions for the existence of asymptotic synchronization controllers, considering practical engineering factors such as actuator failures. Finally, the effectiveness of this approach is validated through a numerical example.