RBFNN-Based Adaptive Fixed-Time Sliding Mode Tracking Control for Coaxial Hybrid Aerial–Underwater Vehicles Under Multivariant Ocean Disturbances

RBFNN-Based Adaptive Fixed-Time Sliding Mode Tracking Control for Coaxial Hybrid Aerial–Underwater Vehicles Under Multivariant Ocean Disturbances

In this study, the design of an adaptive neural network-based fixed-time control system for a novel coaxial trans-domain hybrid aerial–underwater vehicle (HAUV) is investigated. A radial basis function neural network (RBFNN) approximation strategy-based adaptive fixed-time terminal sliding mode cont...

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Bibliographic Details
Main Authors: Mingqing Lu, Wei Yang, Zhenyu Xiong, Fei Liao, Shichong Wu, Yumin Su, Wenhua Wu
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Drones
Subjects:
coaxial HAUV
trans-media motion
fixed-time sliding mode control
adaptive technique
RBFNN
online model identification
Online Access:https://www.mdpi.com/2504-446X/8/12/745
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