An Observer-Based Distributed Adaptive Control Algorithm for Coordination of Multiagent Systems in the Presence of Coupled Dynamics

In this paper, a distributed adaptive control algorithm is designed for an uncertain multiagent system in the presence of unmeasurable coupled dynamics that adopts user-assigned Laplacian matrix nullspaces. Specifically, we use observer dynamics that help us to guarantee the overall system stability, low-frequency learning methods to deal with high-frequency learning, and a modified Laplacian matrix to coordinate the multiagent system. Our algorithm proposes the coordination of multiagent systems and an asymptotic decoupling approach. An illustrative numerical example is given to demonstrate our theoretical contributions.