Adaptive Event-Triggered Attitude Consensus With Prescribed-Time Convergence

This article addresses the event-triggered attitude consensus problem for multiple rigid body systems with prescribed-time convergence. Achieving event-triggered prescribed-time attitude consensus almost globally is challenging in the attitude configuration space which is a non-Euclidean manifold. We design an adaptive event-triggered attitude consensus framework by using the exponential coordinates through the logarithm mapping covering $\mathbb {SO}(3)$ almost globally. A novel triggering strategy governed by a dynamic variable is proposed to reduce the triggering numbers and guarantee the convergence performance simultaneously. With the proposed adaptive control framework, we achieve almost global attitude consensus with prescribed-time convergence in the event-triggered sampling setting with undirected graphs. Compared to existing results, the proposed adaptive control framework ensures event-triggered prescribed-time attitude consensus in a fully distributed manner, suggesting that the proposed framework does not rely on the global knowledge of the entire topology. Finally, we conduct numerical simulations to validate our results.