A unified inner-/outer-loop distributed design for task-space robust cooperative tracking of uncertain networked manipulators under directed graphs

This paper investigates task-space cooperative tracking of networked manipulators with an inner-/outer-loop closed control architecture, taking effects of uncertain kinematics, dynamics, disturbances, and unavailable task-space velocities into account. In the existing related works, the developed distributed cooperative control algorithms require either an open control architecture with torque-based controllers or the combination of inner/outer loop to be stable with the effects of unknown dynamics being neglected. In contrast, in this work we propose a novel distributed control framework such that a distributed outer-loop adaptive scheme is developed to achieve task-space robust cooperative tracking with dynamic effects being considered and without modifying the inner control loop. In particular, a distributed estimator is firstly developed to estimate the desired global task. With this estimated information, distributed cooperative algorithms are presented for two types of inner-loop controllers to ensure task-space coordinated tracking asymptotically. If the robot has an open control architecture, the torque-based distributed controller is provided for task-space cooperative tracking, which can cover existing related results as a special case. Finally, numerical simulations are provided to show the effectiveness of the proposed designs.