 The paper discusses a design problem for a robust adaptive gain controller for multi-agent systems with uncertainties. The controller reduces the effects of uncertainties on the relative distances between agents while still maintaining consensus. It does so by considering the relative distances between the leader and follower agents, and using fixed gains and variable gains that are tuned over time based on the current state of the system. Sufficient conditions for the existence of the controller are reduced to solving linear matrix inequalities, LMI's, and the controller's effectiveness is demonstrated through numerical simulations. This article was authored by Shun Ito, Keiru Ohara, Yashikatsu Hoshi, and others.