Trajectory Tracking Control for a Remotely Operated Vehicle Based on Cascade Model Predictive Control

Nowadays, more and more remotely operated vehicles are applied in the underwater explorations. Tracking control is essential in certain tasks such as pipeline inspections. In this paper, a cascade model predictive control is proposed for the tracking control of a remotely operated vehicle. Then, we compare the proposed cascade model predictive control and the integration of model predictive control and sliding mode control through simulation. Their performances in the tracking of planar and spatial trajectories will be compared to verify the differences. The cascade model predictive control is experimentally proven to outperform the integration of model predictive control and sliding mode control in terms of convergence speed and simulation run time.