  In this paper, we study a distributed optimization problem for a class of
high-order multi-agent systems with unknown dynamics. In comparison with
existing results for integrators or linear agents, we need to overcome the
difficulties brought by the unknown nonlinearities and also the optimization
requirement. For this purpose, we employ an embedded control based design and
first convert this problem into an output stabilization problem. Then, two
kinds of adaptive controllers are given for these agents to drive their outputs
to the global optimal solution under some mild conditions. Finally, we show
that the estimated parameter vector converges to the true parameter vector
under some well-known persistence of excitation condition. The efficacy of
these algorithms was verified by a simulation example.
