A local state emulator-based adaptive control law is proposed for multiagent systems with agents having linear time-invariant dynamics. Specifically, we present and analyze a distributed adaptive control architecture, where agents achieve system-level goals in the presence of exogenous disturbances. Apart from existing relevant literature that makes specific assumptions on network topologies, agent dynamics, and/or the fraction of agents subjected to disturbances, the proposed approach allows agents to achieve system-level goals — even when all agents are subject to exogenous disturbances. Several numerical examples are provided to demonstrate the efficacy of our approach.
