Alpha-Matrix Adaptive Model-Free Control for Quadrotor with Manipulator Under Wind Disturbance

This article develops a-matrix adaptive model-free control (am-AMFC) based on time delay estimation (TDE) for manipulating the position and attitude of an aerial manipulator. The system is composed of a quadrotor and a two-degree-of-freedom(2-DOF) manipulator, and it functions in the presence of friction and wind disruption. The referred am-AMFC is developed using a TDE-based intelligent PD control (TDE-iPD) and an αm online adaptive estimation law. The TDE is intended to offer estimations of the system state, model uncertainties, and lumped disturbances of the system. αm is adaptively updated by forgetting factor recursive least square (FFRLS). Finally, Lyapunov function is used to analyze the stability of the system. Numerical simulations were conducted to illustrate the efficacy of the am-AMFC controller in comparison to PID and TDE-iPD controllers.

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Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/icrcv62709.2024.10758605
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.00

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Controls
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article

Alpha-Matrix Adaptive Model-Free Control for Quadrotor with Manipulator Under Wind Disturbance

Xincheng Zhuang, Haoping Wang, Ding Ding, Yang Tian
Adaptive Control of Nonlinear Systems
article

Alpha-Matrix Adaptive Model-Free Control for Quadrotor with Manipulator Under Wind Disturbance

Xincheng Zhuang, Haoping Wang, Ding Ding, Yang Tian
article en

Abstract

This article develops a-matrix adaptive model-free control (am-AMFC) based on time delay estimation (TDE) for manipulating the position and attitude of an aerial manipulator. The system is composed of a quadrotor and a two-degree-of-freedom(2-DOF) manipulator, and it functions in the presence of friction and wind disruption. The referred am-AMFC is developed using a TDE-based intelligent PD control (TDE-iPD) and an αm online adaptive estimation law. The TDE is intended to offer estimations of the system state, model uncertainties, and lumped disturbances of the system. αm is adaptively updated by forgetting factor recursive least square (FFRLS). Finally, Lyapunov function is used to analyze the stability of the system. Numerical simulations were conducted to illustrate the efficacy of the am-AMFC controller in comparison to PID and TDE-iPD controllers.

Nanjing University of Science and Technology (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 75%
Adaptive Control of Nonlinear Systems
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