In this paper, a model predictive control (MPC) method optimized by an adaptive particle swarm optimization (APSO) algorithm is proposed. Combined with non-singular terminal sliding mode control (NTSMC), the inner and outer double-closed-loop control system is constructed to solve the fully actuated autonomous underwater vehicle (AUV) dynamic trajectory tracking control problem. First, the outer loop controller generates the expected optimal velocity commands and passes them to the inner loop velocity controller, which generates the available control inputs to ensure the entire closed-loop trajectory tracking. In the controller design stage, system input and state constraints are effectively considered. After that, a compensator based on an adaptive radial basis function (RBF) neural network (NN) is designed to compensate for the model error and external sea state disturbances and to improve the control accuracy of the system. Then, the stability of the proposed controller is proved based on Lyapunov analysis. Finally, the dynamic trajectory tracking performance of an AUV with different sea state disturbances is verified by simulation, and the simulation results are compared with double-closed-loop PD control and cascade control of standard MPC based on PSO and SMC. The results show that the designed controller is effective and robust.

The composition characteristics and working principle of the hydraulic rotary system of the azimuth thruster were analyzed. The mathematical model of the rotary dynamic system of the pump-controlled hydraulic motor driving the gear reduction mechanism was established. Additionally, a fast tracking method for the azimuth angle of the azimuth thruster was proposed to analyze the rotary azimuth angle, angular velocity and dynamic response characteristics of the hydraulic system for different desired azimuth angles. The simulation results show that the established dynamic model can simulate the rotary motion response process of the real thruster, and can realize the rapid and accurate tracking of the azimuth angle. At the same time, the physical constraints of the rotary dynamic response were established. It provides an important reference for research on the motion control methods of dynamic positioning vessels.