Fuzzy Fixed-Time Event-Triggered Consensus Control for Uncertain Nonlinear Multiagent Systems With Memory-Based Learning

This article aims to address the issue of fixed-time consensus control for uncertain nonlinear multiagent systems (MASs), in which only a group of followers can directly access the leader's information. To ensure the minimum utilization of wireless channel without sacrificing system performance, a fixed-time event-triggered consensus scheme is developed and employed. First, the fixed-time observer with the event-triggered mechanism is proposed to estimate the states of the leader for each follower, which eliminates the unexpected Zeno behavior. Then, based on the reconstructed leader's information, a fuzzy fixed-time controller via memory-based learning is proposed, in which the fuzzy logic system (FLS) technology is utilized to handle the uncertainty in the MASs. Unlike most FLS-based results, the historical memory instead of the single data point is utilized to update the FLS, which improves the learning ability of FLS. Moreover, in the proposed distributed controller, only one FLS parameter is required to be updated for each
$n$
-order uncertain follower, effectively improving the computational efficiency. With the help of graph theory and Lyapunov stability theory, the fixed-time stability for the entire system is derived. Finally, the validity of the proposed control scheme is illustrated through simulation examples.