Fixed-Time Filtered Adaptive Parameter Estimation and Attitude Control for Quadrotor UAVs

In this article, a fixed-time filtered adaptive parameter estimation and control scheme is proposed for attitude tracking of quadrotor unmanned aerial vehicles. A nonsingular fixed-time sliding mode surface is constructed to avoid the existence of the singularity issue resulted from the differentiat...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2022-10, Vol.58 (5), p.4135-4146
Main Authors: Tao, Meiling, Chen, Qiang, He, Xiongxiong, Xie, Shuzong
Format: Article
Language:English
Subjects:
Adaptation models
Adaptive control
Adaptive fixed-time control
Angular velocity
Attitude control
attitude tracking
Continuity (mathematics)
Control systems design
Controllers
Convergence
fixed-time parameter convergence
Parameter estimation
quadrotors
Singularities
Sliding mode control
Stability analysis
Tracking errors
Uncertainty
Unmanned aerial vehicles
Unmanned helicopters
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Summary:In this article, a fixed-time filtered adaptive parameter estimation and control scheme is proposed for attitude tracking of quadrotor unmanned aerial vehicles. A nonsingular fixed-time sliding mode surface is constructed to avoid the existence of the singularity issue resulted from the differentiation of the sliding mode variable. Through designing auxiliary filtered matrices, a fixed-time parameter update law is developed to achieve the fixed-time parameter convergence. Then, an adaptive neural controller is designed to ensure the fixed-time convergence of attitude tracking errors in the presence of the model uncertainties. Instead of using any piecewise continuous functions, the possible singularity issue in the conventional fixed-time controller design can be overcome by constructing auxiliary functions, and thus the fixed time stability analysis becomes more concise. The efficiency of the presented scheme is validated through experiments on a practical Quanser quadrotor platform.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2022.3159770