Journal ArticleDOI
Adaptive Dynamic Surface Control for Formations of Autonomous Surface Vehicles With Uncertain Dynamics
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TLDR
A robust adaptive formation controller is developed by employing neural network and dynamic surface control technique and is able to capture the vehicle dynamics without exact information of coriolis and centripetal force, hydrodynamic damping and disturbances from the environment.Abstract:
In this brief, we consider the formation control problem of underactuated autonomous surface vehicles (ASVs) moving in a leader-follower formation, in the presence of uncertainties and ocean disturbances. A robust adaptive formation controller is developed by employing neural network and dynamic surface control technique. The stability of the design is proven via Lyapunov analysis where semiglobal uniform ultimate boundedness of the closed-loop signals is guaranteed. The advantages of the proposed formation controller are that: first, the proposed method only uses the measurements of line-of-sight range and angle by local sensors, no other information about the leader is required for control implementation; second, the developed neural formation controller is able to capture the vehicle dynamics without exact information of coriolis and centripetal force, hydrodynamic damping and disturbances from the environment. Comparative analysis with a model-based approach is given to demonstrate the effectiveness of the proposed method.read more
Citations
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Journal ArticleDOI
Unmanned surface vehicles: An overview of developments and challenges
TL;DR: An overview of both historical and recent USVs development is provided, along with some fundamental definitions, and existing USVs GNC approaches are outlined and classified according to various criteria, such as their applications, methodologies, and challenges.
Journal ArticleDOI
Adaptive Neural Network Control of AUVs With Control Input Nonlinearities Using Reinforcement Learning
TL;DR: The trajectory tracking problem for a fully actuated autonomous underwater vehicle (AUV) that moves in the horizontal plane is investigated and two neural networks, including a critic and an action NN, are integrated into the adaptive control design.
Journal ArticleDOI
Fault tolerant finite-time leader-follower formation control for autonomous surface vessels with LOS range and angle constraints
TL;DR: It is shown that under the proposed control method, despite the presence of actuator faults and system uncertainties, the formation tracking errors can converge into arbitrarily small neighborhoods around zero in finite time, while the constraint requirements on the LOS range and angle will not be violated.
Journal ArticleDOI
Distributed Maneuvering of Autonomous Surface Vehicles Based on Neurodynamic Optimization and Fuzzy Approximation
Zhouhua Peng,Jun Wang,Dan Wang +2 more
TL;DR: It is proven that distributed maneuvering errors converge to a residual set by virtue of cascade stability analysis, and an optimization-based command governor is employed to generate an optimal guidance signal for vehicle kinetics.
Journal ArticleDOI
Output-Feedback Path-Following Control of Autonomous Underwater Vehicles Based on an Extended State Observer and Projection Neural Networks
Zhouhua Peng,Jun Wang +1 more
TL;DR: Simulation results substantiate the efficacy of the proposed method for output-feedback path-following of under-actuated autonomous underwater vehicles and prove that all error signals in the closed-loop system are uniformly and ultimately bounded.
References
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Proceedings ArticleDOI
An Adaptive Vision-based Approach to Decentralized Formation Control
TL;DR: Presented at the AIAA Guidance, Navigation, and Control Conference and Exhibit 16 - 19 August 2004, Providence, Rhode Island.
Proceedings ArticleDOI
Sliding mode formation control for under-actuated autonomous surface vehicles
TL;DR: In this article, the authors proposed a sliding mode control law for controlling multiple UAVs in arbitrary formations using only local sensor-based information, where each vehicle only has two actuators and the vehicles are under-actuated.
Proceedings Article
Robust adaptive formation control with autonomous surface vehicles
TL;DR: Based on Lyapunov synthesis, the proposed adaptive NN control ensures that both relative distance and angle track the given bounded reference signals to a small neighborhood of zero as discussed by the authors, where neural networks are trained online to compensate for uncertainties due to unknown velocity of the leader.
Proceedings ArticleDOI
Filtering robust adaptive formation guidance law with uncertain leader dynamics
TL;DR: In this article, a new filtering robust adaptive formation guidance law is proposed for unmanned surface vehicles (USVs) in the presence of uncertain leader dynamics using the approximation properties of neural network (NN) and adaptive bounding technique.