A performance guaranteed sampled-data event-triggered consensus approach for linear multi-agent systems

Abstract

The paper proposes a novel performance guaranteed sampled-data event-triggered consensus (PSEC) algorithm for linear multi-agent systems configured as directed networks. To reduce information exchanges and preserve communication resources, a sampled-data event detector is incorporated at each agent. Communication between agents is based on the fulfillment of distributed state-dependent event-triggering conditions. PSEC ensures a guaranteed exponential convergence rate and is resilient to norm-bounded uncertainties in control gains resulting from implementation distortions. The Lyapunov–Krasovskii theorem is used to incorporate the performance objectives. The design parameters, namely, the heterogeneous control gains and a transmission threshold, are simultaneously computed using a constrained convex optimization framework with linear matrix inequalities. Numerical simulations based on an experimental spacecraft formation flying multi-agent system quantify the effectiveness of the proposed PSEC approach.