Variable buoyancy control for a bottom skimming autonomous underwater vehicle

Two feedback controllers are presented that utilize data averaging and model-based estimation to offset the effects of sensor noise and achieve precise control of an autonomous underwater vehicle (AUV) variable buoyancy system (VBS). Operation of the bottom skimming AUV requires a constant reaction force between the seabed and the vehicle. While performing a mission, variable seafloor topography and a changing payload weight requires the use of a VBS to maintain the reaction force. Two traits of the VBS system that make this a challenging problem are the presence of sensor noise and fast on/off actuation relative to the sensor update rate. It was discovered that both controllers function under these conditions but the model-based controller provides more precise control of the system. This paper presents a comparison between these two control algorithms based on both simulation results and field experiments in a coastal environment.