In　this　article,　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　techniques.　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.