Disturbance-Observer-Based Control and Related Methods—An Overview

TLDR

Disturbance‑observer‑based control (DOBC) and related methods have been researched and applied across diverse industrial sectors for over four decades, typically treating disturbance and uncertainty together and estimating the combined effect via an observation mechanism. This survey systematically reviews and summarizes disturbance/uncertainty estimation and attenuation techniques—including DOBC, active disturbance rejection control, disturbance accommodation control, and composite hierarchical antidisturbance control—while comparing compensation strategies and integration procedures with predesigned linear or nonlinear controllers. The authors provide concise tutorials of the main methods, detailing their features, and discuss how to integrate disturbance/uncertainty compensation into existing controllers. The survey reviews industrial applications of these methods, highlighting commercialization of several algorithms, and concludes with proposed future research directions.

Abstract

Disturbance-observer-based control (DOBC) and related methods have been researched and applied in various industrial sectors in the last four decades. This survey, at first time, gives a systematic and comprehensive tutorial and summary on the existing disturbance/uncertainty estimation and attenuation techniques, most notably, DOBC, active disturbance rejection control, disturbance accommodation control, and composite hierarchical antidisturbance control. In all of these methods, disturbance and uncertainty are, in general, lumped together, and an observation mechanism is employed to estimate the total disturbance. This paper first reviews a number of widely used linear and nonlinear disturbance/uncertainty estimation techniques and then discusses and compares various compensation techniques and the procedures of integrating disturbance/uncertainty compensation with a (predesigned) linear/nonlinear controller. It also provides concise tutorials of the main methods in this area with clear descriptions of their features. The application of this group of methods in various industrial sections is reviewed, with emphasis on the commercialization of some algorithms. The survey is ended with the discussion of future directions.