This article proposes and analyses distributed, leaderless, model-independent consensus algorithms for networked Euler-Lagrange systems. We propose a fundamental consensus algorithm, a consensus algorithm accounting for actuator saturation, and a consensus algorithm accounting for unavailability of measurements of generalised coordinate derivatives, for systems modelled by Euler-Lagrange equations. Due to the fact that the closed-loop interconnected Euler-Lagrange equations using these algorithms are non-autonomous, Matrosov's theorem is used for convergence analysis. It is shown that consensus is reached on the generalised coordinates and their derivatives of the networked Euler-Lagrange systems as long as the undirected communication topology is connected. Simulation results show the effectiveness of the proposed algorithms.