Fully distributed observer-based scaled consensus of multi-agent systems with actuator saturation and edge-based event-triggered communication

This work uses an edge-based event-triggered technique to study the adaptive scaled consensus of general linear multi-agent systems with actuator saturation and unmeasurable internal states. By proposing an edge-based event-triggered scaled algorithm, constructing an improved Lyapunov function, and introducing a low-gain feedback technique, the difficulties generated by actuator saturation and scaling property are overcome, and a triggering condition based on the triggering function is obtained, under which the scaled consensus is achieved, and the Zeno behavior is excluded. This work's results are more flexible than existing results; in other words, triggering numbers and convergence rates are adjusted in this work. Finally, several examples are proposed to verify the results and their interesting characteristics.