Distributed coordinated tracking control of multiple Euler-Lagrange systems by state and output feedback

This study addresses the distributed state and output feedback coordinated tracking problem for multiple Euler-Lagrange systems with a moving leader in the presence of non-linear uncertainties under a directed topology graph. The authors first design a distributed coordinated tracking control scheme by full-state feedback, where each follower can only share information with its neighbours. Next, the adaptive neural networks are applied to deal with the model uncertainties due to their superior approximation capability. To deal with the absence of velocity sensors, then they propose a distributed output feedback coordinated tracking control law combined with a high-gain observer. The uniform ultimate boundedness of all the state errors can be guaranteed in the sense of Lyapunov stability theory. Furthermore, the leaderless synchronisation problem is solved using the proposed control schemes. Finally, simulation examples are presented to illustrate the feasibility of the theoretical results.