Adaptive consensus tracking of first-order multi-agent systems with unknown control directions

Abstract

A novel control algorithm based on Nussbaum function is proposed to settle the adaptive consensus tracking for first-order multi-agent systems with completely non-identical unknown control directions (UCDs) and uncertainties under connected undirected graphs or balanced and weakly connected digraphs in this paper. The Nussbaum function is introduced in the distributed control law to settle the UCDs of multi-agent systems. Then, it is proven that multi-agent systems with UCDs and uncertainties can achieve asymptotic consensus and reach the target state under the assumption that the underlying topology is undirected graphs or balanced and weakly connected graphs. Finally, theoretical and simulation results has verified the validity of our proposed algorithm.