Trajectory Tracking Control of an Underwater Swimming Manipulator with State Constraints

The underwater swimming manipulator is a new type of underwater vehicle manipulator composed of an underwater snake robot and several thrusters. In this paper, trajectory tracking control is considered for the USM system with state constraints and model uncertainties. The barrier Lyapunov function combined with the backstepping method is introduced to design an adaptive controller to guarantee the state constraints satisfaction. The radial basis function neural networks are employed to approximate the unknown system parameters and external disturbances to enhance the robustness of the system. By Lyapunov stability theory analysis, it is proved that the closed-loop system is semi-globally uniformly bounded. Furthermore, the effectiveness of the proposed method is verified with simulation.