Intermittent model predictive control of an autonomous underwater vehicle

The autonomous underwater vehicles (AUVs) have been developed over the last three decades for potential uses in scientific, commercial, environmental, and military purposes. The improvement of the computer technology has allowed the expansion of control algorithms into untethered AUVs motions. The paper applies the continuous time model predictive control algorithm designed using Laguerre functions to the dynamic motions of the vehicle. The nonlinear model of the AUVs is established in six degree of freedom and converts into a state space model. The continuous time model predictive control (MPC) algorithm, using Laguerre orthogonal functions, is extended to include intermittent features for manipulation of rudder and stern angle signals. The proposed approach allows the continuous time MPC to tolerate slower computational time and longer sampling interval