Event-Triggered Optimal Tracking Control for Underactuated Surface Vessels via Neural Reinforcement Learning

This article presents a prescribed-time tracking control method for underactuated unmanned surface vessels (USVs) using a neural reinforcement learning (RL) approach. First, the hand position approach, addressing the underactuated characteristic, is employed to convert the model of USV into the inte...

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Veröffentlicht in:	IEEE transactions on industrial informatics 2024-11, Vol.20 (11), p.12837-12847
Hauptverfasser:	Liu, Xiang, Yan, Huaicheng, Zhou, Weixiang, Wang, Ning, Wang, Yueying
Format:	Artikel
Sprache:	eng
Schlagworte:	Backstepping Event-trigger Informatics Navigation optimized backstepping control prescribed performance control (PPC) Reinforcement learning reinforcement learning (RL) Trajectory Underactuated surface vessels unmanned surface vessels (USVs) Vectors
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