Modern applications of robotics typically involve a robot control system with an inner PI (proportional-integral) or PID (proportional-integral-derivative) control loop and an outer user-specified control loop. The existing outer loop controllers, however, do not take into consideration the dynamic effects of robots and their effectiveness relies on the ad hoc assumption that the inner PI or PID control loop is fast enough, and other torque-based control algorithms cannot be implemented in robotics with closed architecture (i.e., the torque control loop is closed). In this paper, we propose a dynamic modularity approach to resolve this issue, and a class of adaptive outer loop control schemes is proposed for robotic systems with an inner/outer loop structure and their role is to generate joint velocity and position commands for the low-level joint servoing loop. Without relying on the ad hoc assumption that the joint servoing is fast enough or the modification of the low-level joint controller structure, we rigorously show that the proposed outer loop controllers can ensure the stability and convergence of the closed-loop robotic system. We also propose the outer loop version of the standard Slotine and Li adaptive controller in joint space, and a promising conclusion may be that most torque-based adaptive controllers for robots can be redesigned to fit the inner/outer loop structure, by using the adaptively scaled dynamic compensation and the new definition of the joint velocity command. Simulation results are provided to show the performance of the proposed adaptive outer loop controllers, using a three-DOF (degree-of-freedom) manipulator.
['Hanlei Wang', 'Wei Ren', 'Chien Chern Cheah', 'Yongchun Xie']
Dynamic modularity approach to adaptive inner/outer loop control of robotic systems