An Event-Triggered Distributed Control Architecture for Scheduling Information Exchange in Networked Multiagent Systems

In the design and implementation of networked multiagent systems, it is essential not only to guarantee closed-loop system stability but also to schedule interagent information exchange in order to prevent potential network overload and decrease wireless communication costs. For stably scheduling information exchange in networked multiagent systems, the contribution of this article is threefold. We first present a new event-triggered distributed control architecture predicated on a dynamic threshold, which involves an error signal between the state of an agent and the state of its reference model as well as an exponentially decaying term, to schedule interagent information exchange. Building upon the first contribution and in contrast to the standard sampled data exchange viewpoint when an event occurs, second, we propose a method entitled solution-predictor curve. In particular, this method approximates the solution trajectory related to information exchange, where every agent stores this curve and distributively exchanges its parameters when an event occurs. Its key feature is that each agent utilizes the resulting solution trajectory over the time interval until the next event occurs, where it has the capability to further reduce interagent information exchange compared with the sampled data case. A system-theoretical stability analysis of the proposed event-triggered distributed control architecture is given, which captures both sampled data and solution-predictor curve cases, and practical guidelines on the selection of parameter tuning parameters are also stated. As the third contribution, we demonstrate the efficacy of our theoretical results in laboratory-level experiments.