Distributed coordinated control of networked robotic systems formulated by Lagrange dynamics has recently been a subject of considerable interest within science and technology communities due to its broad engineering applications involving complex and integrated production processes,where high flexibility,manipulability,and maneuverability are desirable characteristics.In this paper,we investigate the distributed coordinated adaptive tracking problem of networked redundant robotic systems with a dynamic leader.We provide an analysis procedure for the controlled synchronization of such systems with uncertain dynamics.We also find that the proposed control strategy does not require computing positional inverse kinematics and does not impose any restriction on the self-motion of the manipulators;therefore,the extra degrees of freedom are applicable for other sophisticated subtasks.Compared with some existing work,a distinctive feature of the designed distributed control algorithm is that only a subset of followers needs to access the position information of the dynamic leader in the task space,where the underlying directed graph has a spanning tree.Subsequently,we present a simulation example to verify the effectiveness of the proposed algorithms. Distributed coordinated control of networked robotic systems formulated by Lagrange dynamics has recently been a subject of considerable interest within science and technology communities due to its broad engineering applications involving complex and integrated production processes, where high flexibility, manipulability, and maneuverability are desirable characteristics. this paper, we investigate the distributed coordinated adaptive tracking problem of networked redundant robotic systems with a dynamic leader. We provide an analysis procedure for the controlled synchronization of such systems with uncertain dynamics.We also find that the proposed control strategy does not require computing positional inverse kinematics and does not impose any restriction on the self-motion of the manipulators; therefore, the extra degrees of freedom are applicable for other sophisticated subtasks. Compared with some existing work, a distinctive feature of the designed distributed control algorithm is that only a subset of followers needs to access the position information of the dynamic leader in the task space, where the underlying directed graph has a spanning tree. Substituted, we present a simulation example to verify the effectiveness of the proposed algorithms.