Affine Formation Control from Data

Different from existing works that require information of dynamic models, this paper investigates how to achieve distributed affine formation control without such information. First, a leader-follower framework is introduced, which forms the basis for a data-driven distributed protocol that enables followers to form a time-varying target formation. This method removes the necessity for followers to employ estimators to obtain information about the target formation. Second, by addressing both noise-free and noisy data scenarios, data-based stability criteria for multi-agent systems are developed, with the control gain matrices derived.