A Guide for Gain Tuning of Disturbance Observer: Balancing Disturbance Estimation and Noise Suppression

摘要

This paper presents a general guideline for gain tuning of nonlinear disturbance observer (DO). Receding-horizon optimization based upon a performance index including both disturbance estimation and noise suppression, is adopted. The proposed approach mainly exhibits the following two attractive features. First, an explicitly analytical form of DO gains with the weights in the performance index is given; thus, real-time tuning is available. Second, with the intention of optimization, stability and robustness of the estimation error system is guaranteed. The proposed method is illustrated by an application to the position control of a motor servo system.