The problem of distributed coordinated containment control of multiple Euler-Lagrange systems in presence of nonlinear model uncertainties and external disturbances is investigated. The communication topology is a directed graph, the leaders are dynamic and the relative velocity information between agents is unmeasured. Firstly, the relative velocities are chosen as the auxiliary variables and estimate the auxiliary variables through the low-pass filters. Then, the neural-network method is used to approximate and compensate the nonlinear uncertainties of the systems, and the distributed adaptive containment algorithm is proposed. Based on the Lyapunov stability theory, it is proved that the containment errors between leaders and followers are uniformly ultimately bounded. Finally, a simulation example is presented to illustrate the effectiveness of the proposed control method.