An Extended Kalman Filter for Real-Time Estimation and Control of a Rigid-Link Flexible-Joint Manipulator

Abstract

Maximizing the tracking performance of an industrial manipulator requires an accurate expression of manipulator dynamics and efficient model parameterization. These objectives are difficult to achieve in manipulators with flexible joints since link positions typically are not measured. We present in this paper an extended Kalman filter (EKF) observer to estimate manipulator states and couple these estimates to an adaptive rigid-link flexible-joint (RLFJ) controller. In a computer simulation, the EKF-RLFJ controller demonstrated superior tracking performance compared to a traditional adaptive controller. Experimental results for the Mitsubishi PA10-6CE showed improvements in tracking performance using the EKF-RLFJ controller with a 5 kg end-effector payload. Even greater improvements in tracking performance may be achieved in manipulators with significant joint flexibility.