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Distributed fixed-time adaptive control for group hypersonic gliding vehicles based on dynamic event-triggered subject to multisource uncertainties

Published online by Cambridge University Press:  03 October 2025

X. Xing ,
Z. Wang Open the ORCID record for Z. Wang [Opens in a new window] ,
X. Li ,
C. Wei ,
Y. Wang ,
X. Wang  and
X. Ning
X. Xing
Affiliation:
Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an, Shaanxi, China
Z. Wang*
Affiliation:
Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi’an, Shaanxi, China Northwest Institute of Mechanical and Electrical Engineering, Xianyang, Shaanxi, China
X. Li
Affiliation:
Intelligent Game and Decision Laboratory, Academy of Military Sciences, Beijing, China
C. Wei
Affiliation:
Central South University, Changsha, Hunan, China
Y. Wang
Affiliation:
Nanjing Research Institute of Electronics Technology, Nanjing, Jiangsu, China
X. Wang
Affiliation:
Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an, Shaanxi, China
X. Ning
Affiliation:
School of Astronautics, Northwestern Polytechnical University, Xi’an, Shaanxi, China
*
Corresponding author: Z. Wang; Email: wangzheng0905@nwpu.edu.cn
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Abstract

This paper studies a distributed fixed-time dynamic event-triggered formation control framework for a group of hypersonic gliding vehicles (GHGVs) suffering from internal uncertainties and non-affine properties. The main challenge is strong coupling of non-affine nonlinear dynamic with hypervelocity characteristics and multi-source uncertainties make it difficult to design the control protocol. Firstly, by integrating the distributed consensus control strategy, fractional order control theory and dynamic event-triggered mechanism, a framework of fixed-time formation control for GHGVs system is constructed. Secondly, to mitigate the issue of ‘explosion of complexity’ (EI), a fixed-time command filter (FCF) is proposed and a compensative strategy is formulated to tackle the impact of filtering errors. Thirdly, an additional auxiliary differential equation (ADE) is developed to decouple the control input from the status variable. Several radial base function neural networks (RBFNN) are utilised to handle the unknown internal uncertainties. Furthermore, a unique dynamic event-triggered mechanism (DTEM) is introduced for each follower, facilitating seamless transitions between two distinct dynamic threshold strategies. Analysis based on Lyapunov function illustrates that the output tracking error of followers exponentially converges to a small range within a fixed time, and Zeno behaviour is prevented. Finally, several numerical simulations are presented to demonstrate the practicability and meliority of the suggested approach.

Keywords

auxiliary differential equationdynamic event-triggeredfixed-time formation controlgroup of hypersonic gliding vehiclesRBFNN

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Type
Research Article
Information
The Aeronautical Journal , First View , pp. 1 - 26
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Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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