Rapid Optimization of Active Disturbance Rejection Controller Parameters for Quadrotor UAVs Using Kriging Surrogate Modeling

The Active Disturbance Rejection Controller (ADRC), celebrated for its superior resistance to interference, presents itself as an exemplary solution for the development of control systems that are designed to accommodate substantial changes in payload weight for quadrotor Unmanned Aerial Vehicles (UAVs) and to endure robust side winds along with other challenging operational scenarios. Despite the inherent complexity due to the numerous parameters required for the configuration of the ADRC, an innovative method utilizing the Kriging surrogate optimization algorithm has been introduced to automate and expedite the generation of these controller parameters. The development of the ADRC begins with the dynamics model of the quadrotor UAV, followed by the identification of key design parameters. These parameters are then rapidly optimized through the Kriging surrogate optimization algorithm. The controller’s effectiveness is confirmed by implementing the ADRC on Pixhawk flight control hardware, with a comparative analysis of the attitude response under various operating conditions, thereby validating the ADRC’s superior anti-disturbance performance.

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Publication Details

Journal
Drones
Published
2024-11-08
DOI
https://doi.org/10.3390/drones8110658
Citations
4
Primary Topic
Real-time simulation and control systems
Type
article
Field-Weighted Citation Impact
1.31
Controls
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article

Rapid Optimization of Active Disturbance Rejection Controller Parameters for Quadrotor UAVs Using Kriging Surrogate Modeling

Wenya Zhou, Fei Zong, Xinhan Hu, Shuyue Zhang
4 citations
Drones
Real-time simulation and control systems
1.31
article

Rapid Optimization of Active Disturbance Rejection Controller Parameters for Quadrotor UAVs Using Kriging Surrogate Modeling

Wenya Zhou, Fei Zong, Xinhan Hu, Shuyue Zhang
article en
4 citations

Abstract

The Active Disturbance Rejection Controller (ADRC), celebrated for its superior resistance to interference, presents itself as an exemplary solution for the development of control systems that are designed to accommodate substantial changes in payload weight for quadrotor Unmanned Aerial Vehicles (UAVs) and to endure robust side winds along with other challenging operational scenarios. Despite the inherent complexity due to the numerous parameters required for the configuration of the ADRC, an innovative method utilizing the Kriging surrogate optimization algorithm has been introduced to automate and expedite the generation of these controller parameters. The development of the ADRC begins with the dynamics model of the quadrotor UAV, followed by the identification of key design parameters. These parameters are then rapidly optimized through the Kriging surrogate optimization algorithm. The controller’s effectiveness is confirmed by implementing the ADRC on Pixhawk flight control hardware, with a comparative analysis of the attitude response under various operating conditions, thereby validating the ADRC’s superior anti-disturbance performance.

DronesVol. 8(11)
China Academy of Space Technology (CN), Dalian University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 19%
Real-time simulation and control systems
1.31
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