Decentralized adaptive control of robotic systems using uncalibrated joint torque sensors

Abstract

Standard centralized motion controllers for robotic systems require precise model structure for manipulator dynamics. The controlled robot is also sensitive to sensor failure as each joint in robot receives information from sensors of all other joints. In this paper, we present a dynamically smooth adaptive decentralized controller for robotic manipulators where the control law in each joint depends only on local measurements from that joint. The use of possibly un-calibrated joint torque sensors eliminates the need for modeling link dynamics. Global and asymptotic motion tracking is achieved. Simulation examples demonstrate significant improvement in robustness of the controlled system in face of sensor failure.