Robust adaptive neural network trajectory tracking control design for the quadrotor UAV elastic suspension system

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering 2026

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Authors: Sen Yang, Zeyu Zhang, Peng Chang, Jigang Tong, Tian Xie, Jingyi Yan, Na Liu
DOI: 10.1177/09596518261416953
Cited by: 1
References: 26

Abstract

For the problems of difficult position control and load swing reduction caused by external disturbances in the system of quadrotor UAV with suspended load, the approximation ability of radial basis function neural network (RBFNN) algorithm to the unknown function is used to compensate the external disturbances. A new robust adaptive neural network (RANN) trajectory tracking control scheme is designed. The stability of closed-loop system is analyzed through Lyapunov stability theory. Finally, the performance of the proposed control scheme is verified via numerical simulations.

Fields of Study & Subjects

Adaptive Control of Nonlinear Systems Adaptive Dynamic Programming Control Magnetic Bearings and Levitation Dynamics

Publication details

Journal / source
Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering
Publisher
SAGE Publications
Volume
240
Issue
5
Pages
907–917
Publication date
14 February 2026
Language
EN