High-Order and Model Reference Consensus Algorithms in Cooperative Control of MultiVehicle Systems

In this paper we study th-order 3 consensus algorithms, which generalize the existing first-order and second-order consensus algorithms in the literature. We show necessary and sufficient conditions under which each information variable and its higherorder derivatives converge to common values. We also present the idea of higher-order consensus with a leader and introduce the concept of an th-order model-reference consensus problem, where each information variable and its high-order derivatives not only reach consensus, but also converge to the solution of a prescribed dynamic model. The effectiveness of these algorithms is demonstrated through simulations and a multivehicle cooperative control application, which mimics a flocking behavior in birds. DOI: 10.1115/1.2764508