Model Predictive Control of underwater floating-base manipulator systems in rough seas
Despite recent advances in underwater technology, autonomous operation of unmanned underwater vehicles in complex submerged environments and in harsh climate still remains an unsolved problem. The degree of automation in the offshore sector currently remains limited due to the complexity of performing even the simplest station-keeping tasks when subject to wave and currents dominated scenarios. This has a significant impact on the chance to perform systematic and accurate maintenance and inspection operation of submerged structures, with remarkable implications on the survivability and cost of running of oil rigs, renewable energy plants, etc.
This project aims to exploit Model Predictive Control techniques supplemented with accurate, real-time wave data to perform precise compensation of the hydrodynamic disturbances over a short-range control temporal-horizon. Based on this approach, the vehicle will be able to estimate wave perturbations and implement these in the control input over a short time frame. This will enable to perform accurate station-keeping and enable improved manipulation accuracy even in moderately adverse weather.
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