Hierarchical trajectory tracking control for ROVs subject to disturbances and parametric uncertainties. (15th December 2022) - Long, Chengqi
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. Highlights: A hierarchical control scheme is proposed for the trajectory tracking of the ROV. The hierarchical control scheme includes a velocity layer and a position layer. ESKF-MPC is developed to resist adverse effects of disturbances and process noises. ASMC is used to eliminate chattering caused by parametric uncertainties.