Three-Dimensional Prescribed Performance Tracking Control of UUV via PMPC and RBFNN-FTTSMC

To address the search-and-docking problem in multi-stage prescribed performance switching (MPPS) scenarios, this paper presents a novel compound control method for three-dimensional (3D) underwater trajectory tracking control of unmanned underwater vehicles (UUVs) subjected to unknown disturbances. The proposed control framework can be divided into two parts: kinematics control and dynamics control. In the kinematics control loop, a novel parallel model predictive control (PMPC) law is proposed, which is composed of a soft-constrained model predictive controller (SMPC) and hard-constrained model predictive controller (HMPC), and utilizes a weight allocator to enable switching between soft and hard constraints based on task goals, thus achieving global optimal control in MPPS scenarios. In the dynamics control loop, a finite-time terminal sliding mode control (FTTSMC) method combining a finite-time radial basis function neural network adaptive disturbance observer (RBFNN-FTTSMC) is proposed to achieve disturbance estimation and fast convergence of velocity tracking errors. The simulation results demonstrate that the proposed PMPC-FTTSMC approach achieved an average improvement of 33% and 80% in the number of iterations compared with MPC with sliding mode control (MPC-SMC) and traditional MPC methods, respectively. Furthermore, the approach improved the speed of response by 35% and 44%, respectively, while accurately achieving disturbance observation and enhancing the system robustness.

Automated summary

This paper proposes a novel compound control method for 3D underwater trajectory tracking control of unmanned underwater vehicles (UUVs) in multi-stage prescribed performance switching (MPPS) scenarios. The control framework consists of kinematics control and dynamics control. In the kinematics control loop, a parallel model predictive control (PMPC) law is proposed, which enables switching between soft and hard constraints based on task goals. In the dynamics control loop, a finite-time terminal sliding mode control (FTTSMC) method is proposed to estimate disturbance and achieve fast convergence of velocity tracking errors. Simulation results show significant improvements compared to MPC with sliding mode control (MPC-SMC) and traditional MPC methods.