Strong integral-input-to-state stability for cascade-connected systems under periodic event-triggered mechanisms
Junyi Yang, Hao Yu, Feng Xiao · 2021
This paper focuses on analysing the robustness of sampled-data systems subject to a cascade-connected structure. Two kinds of networks are considered in this work: (1) the detection network, which models the network of the relative detections by agents’ onboard sensors; (2) the communication network, which is used to implement the local transmissions of information. Periodic event-triggered mechanisms (PETMs) are used to avoid continuous-time checking of event-triggering conditions. The maximum allowable sampling periods (MASPs) and maximum allowable checking periods (MACPs) are determined to guarantee the strong integral-input-to-state stability of the closed-loop system. Finally, a numerical example is presented to illustrate the effectiveness of the proposed methods.