An Informativity Approach for Data-Driven Distributed Control for Multiagent Systems with Heterogeneous Control Gains

This paper investigates the distributed data-driven consensus problem for discrete-time leader-following multiagent systems (MASs) under external disturbances. To reduce the reliance on global information, two nested double-layer observers are proposed to estimate the leader’s state trajectory. According to the estimation, a local data-driven controller is proposed using the informativity approach. Compared with the existing prior work, the proposed observer-based scheme allows followers to use heterogeneous control gain matrices, thereby eliminating the requirement to solve centralized data-driven inequalities and enhancing the distributed characteristics. The effectiveness of the theoretical results are verified through numerical simulations.