Dynamic Modularity Approach to Adaptive Inner/Outer Loop Control of Robotic Systems
Hanlei Wang, Wei Ren, Chien Chern Cheah, Yongchun Xie, Shangke Lyu

TL;DR
This paper introduces a dynamic modularity approach for adaptive outer loop control in robotic systems, effectively accounting for system dynamics and uncertainties without requiring modifications to the low-level joint controllers.
Contribution
It proposes a novel adaptive outer loop control scheme that ensures stability and convergence, compatible with existing inner loop controllers and applicable to various robot configurations.
Findings
Outer loop controllers guarantee stability and convergence.
Simulation and experimental results validate the approach.
Most torque-based adaptive controllers can be integrated into the new framework.
Abstract
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. This paper investigates the adaptive control of robotic systems with an inner/outer loop structure, taking into full account the effects of the dynamics and the system uncertainties, and both the task-space control and joint-space control are considered. We propose a dynamic modularity approach to resolve this issue, and a class of adaptive outer loop control schemes…
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