Improved velocity estimation using low-performance position and torque sensors with applications in friction compensation control systems

Abstract

Velocity computation based on simple numerical differentiation from a low-resolution position sensor or numerical integration from an imperfect torque sensor may be highly erroneous, especially in the low-velocity or high-acceleration regions. To resolve this problem, a novel approach to obtaining high-performance velocities in these regions is presented. The proposed estimator is based on the framework of the Kalman filter. A switching architecture is used to address the estimation problem, with the sensors functioning under different situations. Experimental results show that the proposed estimator significantly reduces velocity errors in estimation compared with an encoder or torque sensor. A dual-loop control structure is also developed with estimated velocity feedback for application in the friction compensation control system of an inertially stabilized platform. Experimental findings show that the control characteristic significantly improves because the proposed approach enables the rejection of non-linear friction.