Nonlinear model predictive control for hydrobatics: Experiments with an underactuated AUV

Hydrobatic autonomous underwater vehicles (AUVs) can be efficient in range and speed, as well agile maneuvering. They beneficial scenarios such obstacle avoidance, inspections, docking, under-ice operations. However, AUVs are underactuated systems—this means exploiting the system dynamics is key to achieving elegant hydrobatic maneuvers with minimum controls. This paper explores use of model predictive control (MPC) techniques presents new simulation experimental results small SAM AUV. Simulations performed using nonlinear (NMPC) on full AUV provide optimal policies for several Matlab/Simulink. For implementation hardware robot operating system, a linear time varying MPC (LTV-MPC) derived from enable real-time control. In simulations, NMPC LTV-MPC shows promising offer much more strategies than what obtained PID quadratic regulator based controllers terms rise-time, overshoot, steady-state error, robustness. The satisfactory performance validation. further also demonstrates experimentally that run performing maneouvers.