This paper proposes a tracking controller for the formation construction of multiple autonomous surface vessels (ASVs) in the presence of model uncertainties and external disturbances with output constraints. To design a formation control system, the leader-following strategy is adopted for each ASV. A symmetric barrier Lyapunov function (BLF), which advances to infinity when its arguments reach a finite limit, is applied to prevent the state variables from violating constraints. An adaptive-neural technique is employed to compensate uncertain parameters and unmodeled dynamics. To overcome the explosion of differentiation term problem, a first-order filter is proposed to realize the derivative of virtual variables in the dynamic surface control (DSC). To estimate the leader velocity in finite time, a high-gain observer is effectively employed. This approach is adopted to reveal all signals of the closed-loop system which are bounded, and the formation tracking errors are semi-globally finite-time uniformly bounded. The computer simulation results demonstrate the efficacy of this newly proposed formation controller for the autonomous surface vessels.

This paper proposes a novel real-time formation control and obstacle avoidance algorithm for multiple fixed-wing UAVs. A formation control algorithm is designed by a combination of the virtual structure, leader-follower, and artificial potential fields methods and harnessing the advantages of those approaches. The kinematic and dynamic constraints of fixed-wing UAVs are considered in the path planning. The performance of the proposed algorithm is examined through simulation in Matlab software by applying the translational dynamics of fixed-wing UAVs. Simulations of different complex scenarios demonstrate the effectiveness of the presented formation flight algorithm through generating multiple efficient paths, which are fully consistent with the functional constraints of the UAVs in the presence of obstacles.