Adaptive Event-triggered Data-driven Consensus Control for Nonlinear Multi-agent Systems

The event-triggered consensus problem for non-linear nonaffine multi-agent systems is examined, wherein the agents communicate in a weakly connected topology and utilize distributed data buffers to minimize the frequency of data refresh in the controller. A dynamic event-triggering mechanism is developed by introducing an adaptive threshold parameter, and a data-driven control protocol is proposed based on locally available information. Specifically, the dynamic rule for adjusting the threshold is designed to balance event occurrences and control performance. Theoretical analysis is rigorously conducted using similarity transformation theorems and properties of the Laplacian matrix. Finally, a simulation example is provided to illustrate the effectiveness of the proposed approach.