Model Predictive Control of Underwater Tethered Payload

A fully automated, buoy-based deployment sensor system is being developed to acquire high-quality water column data, and requires a controller to accurately position an array of sensors at various depths. The sensor system will be potentially deployed under rough ocean conditions. Depth is measured by a pressure sensor and adjusted through a rotating drum powered by a stepper motor. The proposed controller uses a model predictive control algorithm, a type of optimal control that predicts system response to optimize control actions used to track a desired variable-depth, setpoint profile. The profile is calculated to ensure smooth motion of the system, preventing motor malfunction. A simplified system model was created and used to simulate an open-loop test and system response. Constraints were applied to the control actions to match the practical limitations of the stepper motor. The simulated results show successful tracking of both a shallow and deep profile. At this stage of testing, the effects of ocean currents are considered by using a simple disturbance that provides the effect of ocean currents. A practical prototype that can implement the model predictive controller was tested on the physical buoy-based system with good control performance.