Adaptive Model Predictive Control for ROV Routh Tracking in Uncertain Underwater Environments

The intricate and unpredictable nature of underwater environments and disturbances necessitates the use of model predictive control for the effective operation and inspection of Remotely Operated Vehicles (ROVs). This control method effectively counteracts the effects of disturbances and uncertainties. To mitigate the effects of uncertainty, an adaptive controller was developed, targeting uncertainty effects such as hydrodynamic coefficients. This paper presents a model predictive adaptive controller that utilizes Laguerre functions to navigate a designed ship hull cleaning ROV along a predetermined path in the presence of environmental disturbances and uncertainties. The use of Laguerre functions results in efficiency of the proposed controller through successful tracking in an uncertain environment with real disturbance which contained from test. The results highlight the effectiveness of the adaptive MPC design for real-world applications where environmental conditions are unpredictable or subject to change.

Keywords:

Remotely Operated Vehicle , Tracking , Adaptive Model Predictive Control