Semi-global Adaptive Event-triggered Output Feedback Consensus of Linear MASs With Input Saturation

This study explores the adaptive event-triggered output feedback consensus problem in linear multi-agent systems (MASs) subject to input saturation. It provides a semi-global solution without requiring global information on the topology graph for the development of control algorithms. The framework is first introduced for a specific category of networks characterized by a strongly connected graph and is subsequently generalized to the case of a digraph containing a directed spanning tree. The solution is formulated using a low-gain approach, based on the premise that each agent is asymptotically null controllable with bounded controls. Furthermore, the design precludes the occurrence of Zeno behavior. The effectiveness of the proposed control methodologies is demonstrated through numerical simulations.