Auto-Tuning Digital Control Based on Parameters Identification and Disturbance Observer

Abstract

This paper presented a digital servo driver that realizes an auto-tuning feedback and feedforward controller design using on-line parameters identification. Firstly, the variant inertia constant, damping constant and the disturbed load torque of the servo motor are estimated by the recursive least square (RLS) estimator, which is composed of an RLS estimator and a disturbance torque compensator. Furthermore, the auto-tuning algorithm of feedback and feedforward controller is realized according to the estimated parameters to match the tracking specification. The proposed auto-tuning digital servo controllers are evaluated and compared experimentally with a traditional controller on a microcomputer-controlled servo motor positioning system. The experimental results show that this auto-tuning digital servo system remarkably reduces the tracking error.