Norm-free adaptive event-triggering rule for distributed control of multiagent systems

Abstract

We focus on reducing agent-to-agent information exchange in distributed control of multiagent systems. Specifically, our contribution is a norm-free and adaptive event-triggering rule for each agent, where it is decentralised and predicated on the solution-predictor curve method. The decentralised feature means that the proposed event-triggering rule depends on the own error signals of an agent without requiring any neighbouring or global information. The norm-free feature means that the left-hand side of the proposed event-triggering rule inequality does not depend on distances such as absolute values of error signals to allow for better agent-to-agent information exchange reduction. To achieve both decentralised and norm-free features together, an adaptive term is utilised in the event-triggering rule for each agent to estimate unknown variable unavailable to an agent. Here, the presented system-theoretical analysis of the proposed event-triggering rule holds for both the sampled data exchange case and the data exchange case predicated on the solution-predictor curve method. In contrast to standard sampled data exchange, the solution-predictor curve method has the ability to further reduce agent-to-agent information exchange, where each agent stores this curve and exchanges its parameters when an event occurs in a distributed manner for approximating the solution trajectory of each agent.