Internal Model Based Active Disturbance Rejection Control

TL;DR

This paper introduces an internal model based active disturbance rejection control (IADRC) that leverages known disturbance characteristics for perfect estimation, enhancing the robustness and performance over traditional BADRC.

Contribution

The paper proposes a novel IADRC method that exploits known disturbance characteristics to improve disturbance estimation accuracy, addressing a limitation of existing BADRC algorithms.

Findings

IADRC achieves more accurate disturbance estimation than BADRC.

Simulation results demonstrate improved disturbance rejection performance.

The method effectively utilizes known disturbance information under mild assumptions.

Abstract

The basic active disturbance rejection control (BADRC) algorithm with only one order higher extended state observer (ESO) proves to be robust to both internal and external disturbances. An advantage of BADRC is that in many applications it can achieve high disturbance attenuation level without requiring a detailed model of the plant or disturbance. However, this can be regarded as a disadvantage when the disturbance characteristic is known since the BADRC algorithm cannot exploit such information. This paper proposes an internal model based ADRC (IADRC) method, which can take advantage of knowing disturbance characteristic to achieve perfect estimation of the disturbance under some mild assumptions. The effectiveness of the proposed method is validated by comprehensive simulations and comparisons with the BADRC algorithm.