Consensus in Directed Networks of First-order Agents with Unknown High-frequency Gain Signs

In this paper, we study the consensus problem of first-order linearly parameterized agents with unknown high-frequency gain signs. We first propose a class of Nussbaum function based algorithms to deal with the unknown high-frequency gain signs. Then, under the assumption that the graph topology is strongly connected, it is shown that the first-order linearly parameterized agents with unknown high-frequency gain signs can achieve consensus. Finally, an example is provided to verify the proposed algorithms.