UVMS Trajectory Tracking Based on RBFNN and Sliding Mode Control

This article spells out the UVMS trajectory tracking control problem under electric drive. Firstly, based a claim on Radial Basis Function Neural Networks (RBFNN) and Nonsingular Fast Terminal Sliding Mode (NFTSM) methods, the tracking strategy for UVMS is designed. Further, for singularity problem, a saturation-based tracking controller is obtained by means of the methods mentioned above. Lyapunov design is adopted to guarantee the asymptotic stability of the proposed controller. Simulation results show that the tracking consequence of NN-NFTSM is more thoroughly than PD approach and NN approach. The validity and advantages of the proposed controller is testified.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/icist63249.2024.10805389
Citations
1
Primary Topic
Advanced Sensor and Control Systems
Type
article
Field-Weighted Citation Impact
0.33
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UVMS Trajectory Tracking Based on RBFNN and Sliding Mode Control

Weilin Luo, Huan Luo, Yuanjing Wang
1 citations
Advanced Sensor and Control Systems
0.33
article

UVMS Trajectory Tracking Based on RBFNN and Sliding Mode Control

Weilin Luo, Huan Luo, Yuanjing Wang
article en
1 citations

Abstract

This article spells out the UVMS trajectory tracking control problem under electric drive. Firstly, based a claim on Radial Basis Function Neural Networks (RBFNN) and Nonsingular Fast Terminal Sliding Mode (NFTSM) methods, the tracking strategy for UVMS is designed. Further, for singularity problem, a saturation-based tracking controller is obtained by means of the methods mentioned above. Lyapunov design is adopted to guarantee the asymptotic stability of the proposed controller. Simulation results show that the tracking consequence of NN-NFTSM is more thoroughly than PD approach and NN approach. The validity and advantages of the proposed controller is testified.

Fuzhou University (CN)
Affordable and clean energy
Openalex Percentile: Top 37%
Advanced Sensor and Control Systems
0.33
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