Intermittent-Based Fixed-Time Scaled Consensus for Nonlinear Multi-Agent Systems

This article delves into the fixed-time distributed leader-following scaled consensus of nonlinear multi-agent systems (MASs). Firstly, a novel intermittent-based event-triggered algorithm is introduced, where the triggered mechanism relies on the state errors between the current states and the last triggered instants of agents. This approach aims to alleviate computational and communication burdens more efficiently. Secondly, we use the Lyapunov stability theory and various inequality techniques to strictly prove that the state trajectories of all followers converge proportionately to the state of the leader, and Zeno behavior is effectively ruled out. Finally, an example demonstrates the effectiveness and superiority of our proposed algorithm.