# Disturbance Observer-based Robust Control and Its Applications: 35th Anniversary Overview

arXiv: https://arxiv.org/abs/1902.09032 · HTML: https://mlsanity.com/paper/1902.09032/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Feb 2019.

## Built on by (most cited first, 4 of 4)

- [Loss Function Considering Dead Zone for Neural Networks](https://mlsanity.com/paper/2402.00393/) (2024)
- [Quantifying Assistive Robustness Via the Natural-Adversarial Frontier](https://mlsanity.com/paper/2310.10610/) (2023)
- [Quantized Consensus under Data-Rate Constraints and DoS Attacks: A Zooming-In and Holding Approach](https://mlsanity.com/paper/2207.08332/) (2022)
- [Stability-aware Residual Reinforcement Learning Framework for Robotic Manipulator Disturbance Compensation](https://mlsanity.com/paper/2609.21307/) (2026)

## Abstract (arXiv)

Disturbance Observer has been one of the most widely used robust control tools since it was proposed in 1983. This paper introduces the origins of Disturbance Observer and presents a survey of the major results on Disturbance Observer-based robust control in the last thirty-five years. Furthermore, it explains the analysis and synthesis techniques of Disturbance Observer-based robust control for linear and nonlinear systems by using a unified framework. In the last section, this paper presents concluding remarks on Disturbance Observer-based robust control and its engineering applications.