Experimentally verified depth regulation for AUVs using constrained model predictive control

In the application of an autonomous underwater vehicle a critical requirement is to keep the level of the actuation signals within operational limits to avoid, for example, actuator nonlinearities and reduce peak power consumption. The most common approach to this problem for AUVs that have been deployed is, if required, to trade-off performance in order to keep the actuation signals and power required within the operational limits. This paper addresses depth control of an AUV using model predictive control with constraints on the both the amplitude and rate of change of the entries in the control vector. The model predictive control algorithm is designed by solving a quadratic programming problem in real-time when implemented on an AUV prototype. Experimental test results for depth control are also given and demonstrate that physically relevant constraints on the thrust and actuation power, critical factors for the use of these vehicles, can be achieved. Moreover, there is agreement between the control action used and the underlying physics of a body moving in water.