A High‐Order Fully Actuated System Approach for Prescribed Performance Tracking Control of Quadrotor Unmanned Aerial Vehicle With Time‐Varying Uncertain Aerodynamic Parameters and Disturbances

ABSTRACT In this paper, a high‐order, fully actuated (HOFA) system approach‐based adaptive control design, with guaranteed transient and steady‐state tracking performances, is proposed for trajectory tracking of a lightweight, low‐cost quadrotor unmanned aerial vehicle (QUAV). Unlike most existing results on adaptive control for QUAVs, we consider the aerodynamic parameters and disturbance terms of the QUAV model as time‐varying uncertainties. These uncertainties are only assumed to be bounded, with no additional restrictions imposed on their bounds and derivatives, making our approach more suitable for QUAVs in dynamic harsh environments. Moreover, in contrast to the existing first‐order state‐space model‐based methods such as typical adaptive backstepping designs, the proposed HOFA system‐based approach does not require multiple design steps and can achieve arbitrarily assignable eigenstructure like a stabilized linear system, which makes the control design very simple and easy to implement for practical applications. In addition, by introducing the prescribed performance control technique and incorporating a novel appointed‐time performance function, it is shown that all tracking errors can be steered into their predesignated precision regions within their respective pre‐appointed settling times. Finally, the effectiveness and advantages of the proposed method are validated through simulation.

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Institutions

Publication Details

Journal
International Journal of Robust and Nonlinear Control
Published
2024-12-30
DOI
https://doi.org/10.1002/rnc.7793
Citations
4
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
1.31

Funders

Controls
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article

A High‐Order Fully Actuated System Approach for Prescribed Performance Tracking Control of Quadrotor Unmanned Aerial Vehicle With Time‐Varying Uncertain Aerodynamic Parameters and Disturbances

Dandan Zhang, Zhikai Zhang, Chen Yang, Heng Zhang
4 citations
International Journal of Robust and Nonlinear Control
Adaptive Control of Nonlinear Systems
1.31
article

A High‐Order Fully Actuated System Approach for Prescribed Performance Tracking Control of Quadrotor Unmanned Aerial Vehicle With Time‐Varying Uncertain Aerodynamic Parameters and Disturbances

Dandan Zhang, Zhikai Zhang, Chen Yang, Heng Zhang
article en
4 citations

Abstract

ABSTRACT In this paper, a high‐order, fully actuated (HOFA) system approach‐based adaptive control design, with guaranteed transient and steady‐state tracking performances, is proposed for trajectory tracking of a lightweight, low‐cost quadrotor unmanned aerial vehicle (QUAV). Unlike most existing results on adaptive control for QUAVs, we consider the aerodynamic parameters and disturbance terms of the QUAV model as time‐varying uncertainties. These uncertainties are only assumed to be bounded, with no additional restrictions imposed on their bounds and derivatives, making our approach more suitable for QUAVs in dynamic harsh environments. Moreover, in contrast to the existing first‐order state‐space model‐based methods such as typical adaptive backstepping designs, the proposed HOFA system‐based approach does not require multiple design steps and can achieve arbitrarily assignable eigenstructure like a stabilized linear system, which makes the control design very simple and easy to implement for practical applications. In addition, by introducing the prescribed performance control technique and incorporating a novel appointed‐time performance function, it is shown that all tracking errors can be steered into their predesignated precision regions within their respective pre‐appointed settling times. Finally, the effectiveness and advantages of the proposed method are validated through simulation.

International Journal of Robust and Nonlinear ControlVol. 35(6)
Shanghai Ocean University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province
Openalex Percentile: Top 18%
Adaptive Control of Nonlinear Systems
1.31
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