Event-based Consensus Tracking for Nonlinear Multi-Agent Systems under Semi-Markov Jump Topology

This paper studies the event-triggering leader-follower consensus with the strictly dissipative performance for nonlinear multi-agent systems (MASs) with semi-Markov changing topologies. First, a polynomial fuzzy model is established to describe the error nonlinear multi-agent system that is formed by one virtual leader and followers. Then, a new event-triggering transmission strategy is proposed to mitigate communication and computational load. By utilizing the event-triggering mechanism and modeling the switching topologies by semi-Markov process, an event-triggering consensus protocol based on sampled data is designed. Compared with traditional Markov jump topologies, the transition rate is time-varying for semi-Markov switching topologies. By mode-dependent Lyapunov-Krasovskii functional, the sum of square based relaxed stabilization conditions for fuzzy MASs under semi-Markov jump topologies are obtained to guarantee event-triggering consensus in an even-square sense. An illustrative example is provided to verify the proposed consensus design schemes.