This paper addresses the decentralized problem for marine surface vessels (MSVs) in the presence of unknown unmodeled nonlinear dynamics, time-varying external disturbances and input saturations. First, platoon formation is proceeded by using line-of-sight (LOS) guidance. Since each marine vehicle can only acquire information from its immediate predecessor, a symmetric barrier Lyapunov function (BLF) is employed to guarantee the formation errors constrained within a certain range such that leaders and followers can preserve the predefined information structure and ensure the correct steady-state regime. Next, due to the superior approximation capability of an adaptive neural network (NN), we propose a BLF-based controller to deal with the model uncertainties. Further, an auxiliary design system is introduced to compensate for the effect of input saturation. Finally, the uniform ultimate boundedness of all the state errors can be proved and simulation examples are presented to illustrate the effectiveness of the proposed method.

Time-synchronization (TS) formation control for unmanned surface vehicles (USVs) presents several advantages, including precise execution of tasks, broadened combat capabilities, and improved information fusion quality. To achieve this performance, a time-synchronized formation control method is presented that takes into account direct topology, external disturbances, and system uncertainties (EDSU). In contrast to prior formation control strategies, we introduce the formalized time-synchronized formation control framework, where all state components of the formation system concurrently converge to the equilibrium point at a uniform time constant, independently of their initial states. To counteract the EDSU, a fixed-time disturbance observer is designed to guarantee the convergence of all observer error components to zero. System stability is corroborated through the application of Lyapunov-like theory. Simulations and comparative experiments on three USVs are conducted to demonstrate the proposed method's superiority.

A safety guaranteed formation control problem for waterjet unmanned surface vehicles (USV) under the consideration of unmodeled dynamics, environmental disturbances, input saturation, and output constraints is addressed in this paper. The leader-follower method and line-of-sight (LOS) strategy are employed to achieve the desired formation structure. Firstly, two tan-type barrier Lyapunov functions (BLF) are designed to limit the formation errors always within a predefined range to avoid collisions and keep communications, it can also relax the assumption of each USV's initial position to random. Besides, a bioinspired neurodynamics method is involved to avoid the appearance of the virtual velocity differential terms in the control law, which is different from the traditional dynamic surface method and makes it easier to implement in practice. Further, adaptive neural networks (NN) are used to approximate unmodeled dynamics and an auxiliary dynamics system is introduced to handle the input saturation. It is proved that the uniform ultimate boundedness of all signals in the control system can be achieved. Finally, simulation studies show the effectiveness of the proposed control law.

The formation control problem for underactuated unmanned surface vehicles (USVs) is addressed by a distributed strategy based on virtual leader strategy. The control system takes account of disturbance induced by external environment. With the coordinate transformation, the advantage of the proposed scheme is that the control point can be any point of the ship instead of the center of gravity. By introducing bio-inspired model, the formation control problem is addressed with backstepping method. This avoids complicated computation, simplifies the control law, and smoothes the input signals. The system uniform ultimate boundness is proven by Lyapunov stability theory with Young inequality. Simulation results are presented to verify the effectiveness and robust of the proposed controller.

This paper studies the velocity free platoon formation control for unmanned surface vehicles (USVs) with the model uncertainties and output constraints. Firstly, a reconstruction module is designed to estimate the velocity of the leader, which will be completed in finite time and will reduce the communication burden. Along with this, the model-based control combined with the symmetric barrier Lyapunov functions (BLF) method is designed to guarantee the output constraints. Then, the model uncertainties of the USV are approximated by the neural networks (NNs) and the NN BLF control is developed. To achieve the desired formation pattern, the constraints, including collision avoidance and communication distance, are under consideration. Finally, we proved that our system is semiglobally uniformly ultimately bounded (SGUUB) and verified the effectiveness of this approach by simulations.