  In this paper, we investigate a constrained optimal coordination problem for
a class of heterogeneous nonlinear multi-agent systems described by high-order
dynamics subject to both unknown nonlinearities and external disturbances. Each
agent has a private objective function and a steady-state constraint about its
output. We develop a composite distributed controller for each agent by a
combination of internal model and neural network. All agent outputs are proven
to reach the constrained minimal point of the aggregate objective function with
bounded residual errors irrespective of the unknown nonlinearities and external
disturbances. Two examples are finally given to demonstrate the effectiveness
of the algorithm.
