Distributed event-triggered consensus of multi-agent systems with measurement noise and guaranteed interval bounds

Abstract A distributed event-triggered method is developed to reach the consensus with bounded-error measurements. The approach is derived from an initial event-triggered consensus scheme developed in Seyboth et al. (2013). The strategies are presented for single and double-integrator models, considering a fully connected graph. Proofs of convergence to a ball centered at the average consensus value are given. The presence of Zeno behavior is excluded. Guaranteed bounds for consensus are characterized. Results are illustrated with numerical applications.