Hierarchical trajectory tracking control for ROVs subject to disturbances and parametric uncertainties

Abstract

Trajectory tracking control is crucial for a remotely operated underwater vehicle (ROV), but the performance can be degraded due to disturbances, process noises, and parametric uncertainties. Therefore, a hierarchical control scheme is proposed to handle this problem. Firstly, a 4DOF kinematic model and dynamic model of the ROV are constructed. Ocean current disturbance is considered in the kinematic model and the dynamic model when tracking the reference trajectory. Parametric uncertainties are also considered on the dynamic model. Secondly, model predictive control using extended state based Kalman filter (ESKF-MPC) is used to design a kinematic controller (velocity layer) based on the kinematic model to generate virtual expected velocities. ESKF-MPC can not only solve constraints on velocities, but also estimate states and ocean current disturbance, which is beneficial for improving the robustness to ocean current disturbance. Thirdly, adaptive sliding mode control (ASMC) is applied to construct a dynamic controller (position layer) to compute optimal forces and moments based on the dynamic model and virtual expected velocities output by the kinematic controller, which is robust to parametric uncertainties and can solve the chattering problem. Finally, simulations are performed to validate the performance of the proposed hierarchical control scheme.