Model Predictive Control of Tethered Underwater Sensor Payload

A buoy-based 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 deployed to aquaculture sites, potentially in rough ocean conditions. Depth is measured by a pressure sensor and adjusted through a rotating drum powered by a stepper motor. The stepper motor's speed can be controlled by varying the pulse rate sent to the motor driver. The proposed controller uses a model predictive control (MPC) algorithm, a type of optimal control that predicts system response to optimize control actions. The controller determines control actions as pulse rates, which are sent to the motor-drum system to track a desired variable depth set-point 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 sent to the system to match the practical limitations of the stepper motor. The simulated results show successful tracking of both a shallow and deep profile. While the effect of constraining control actions is noticeable in the deeper profile simulation, it does not prevent the system from functioning correctly. At this stage of initial testing, the effects of ocean currents are not considered. Work is ongoing to construct a practical prototype that can implement the model predictive controller on the physical buoy-based system.