Distributed state constraint containment control of multi-AUV formation with unknown control direction

The control problem of multi-autonomous underwater vehicle (multi-AUV) formation systems is a hot issue in current research. The research goal is to make the formation have a more comprehensive ability to deal with emergencies under higher control accuracy. In this paper, input saturation, disturbances, and system uncertainties are considered. To achieve the convergence of system containment errors, a state constraint containment control method is proposed for multi-AUV systems with unknown control direction. Combined with unknown control direction, new auxiliary variables are constructed to compensate the input saturation. On this basis, the follower reference trajectories and errors are defined. To constrain some system states, the tan-type barrier Lyapunov function (TBLF) is proposed. The estimated values of system uncertainties and disturbances can be obtained by neural network. Compared to other works, the amount of data generated by neural network is further reduced by the optimized adaptive law in this study. The unknown control direction problem is handled based on Nussbaum function, and its limitation range is expanded. The designed control method ensures the stable operation of formation systems. The containment errors can converge to a small neighborhood of zero. By comparing the numerical simulation results with other work, the advantages of the control algorithm proposed in this paper has been verified.