Fast finite-time consensus protocol for high-order nonlinear multi-agent systems based on event-triggered communication scheme

This paper proposes an adaptive fast finite-time tracking consensus protocol for high-order nonlinear multi-agent systems. To overcome the limitation of finite-time stability, where the convergence speed slows down when the initial state is far from the origin, the fast finite-time stability theory is incorporated into the multi-agent systems to ensure rapid convergence of the tracking error. Furthermore, the power integrator technique is integrated into the backstepping framework to address the inherent singularity issues in high-order systems. Meanwhile, neural networks are used as online approximators to model unknown nonlinear functions, with the tanh(⋅) function adopted to mitigate the impact of approximation errors effectively. The developed dynamic event-triggered controller can reduce the frequency of control updates, effectively saving communication resources. Finally, two simulation examples demonstrate the effectiveness of the proposed strategy.