scholarly journals Subsea cable tracking by an unmanned surface vehicle

2015 ◽  
Vol 32 (4) ◽  
pp. 217-229 ◽  
Author(s):  
Tomasz Szyrowski ◽  
Amit Motwani ◽  
Sanjay K Sharma ◽  
Robert Sutton ◽  
Gareth A Kennedy
Keyword(s):  
Unmanned Surface Vehicle ◽  
Cable Tracking

Adaptive and extendable control of unmanned surface vehicle formations using distributed deep reinforcement learning

2021 ◽  
Vol 110 ◽  
pp. 102590
Author(s):  
Shuwu Wang ◽  
Feng Ma ◽  
Xinping Yan ◽  
Peng Wu ◽  
Yuanchang Liu
Keyword(s):  
Reinforcement Learning ◽  
Unmanned Surface Vehicle ◽  
Vehicle Formations

Adaptive neural fault-tolerant control for course tracking of unmanned surface vehicle with event-triggered input

2021 ◽  
pp. 095965182110131
Author(s):  
Guoqing Zhang ◽  
Shen Gao ◽  
Jiqiang Li ◽  
Weidong Zhang
Keyword(s):  
Neural Control ◽  
Fault Tolerant ◽  
Lyapunov Stability Theory ◽  
Actuator Faults ◽  
Closed Loop System ◽  
External Disturbances ◽  
Unmanned Surface Vehicle ◽  
Adaptive Parameters ◽  
Control Gain ◽  
Event Triggered

This study investigates the course-tracking problem for the unmanned surface vehicle in the presence of constraints of the actuator faults, control gain uncertainties, and environmental disturbance. A novel event-triggered robust neural control algorithm is proposed by fusing the robust neural damping technique and the event-triggered input mechanism. In the algorithm, no prior information of the system model about the unknown yawing dynamic parameters and unknown external disturbances is required. The transmission burden between the controller and the actuator could be relieved. Moreover, the control gain-related uncertainties and the unknown actuator faults are compensated through two updated online adaptive parameters. Sufficient effort has been made to verify the semi-global uniform ultimate bounded stability for the closed-loop system based on Lyapunov stability theory. Finally, simulation results are presented to illustrate the effectiveness and superiority of the proposed algorithm.

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