Accurate trajectory tracking control of unknown autonomous underwater vehicles: A data-driven predictive approach

Abstract

The adaptive tracking control of autonomous underwater vehicles (AUVs) under the conditions of unavailable kinetic dynamics is considered via developing a new data-driven adaptive predictive control (DAPC) method. By deploying the non-parametric DLT, a new data-based predictive model is first designed such that the unknown kinetic dynamics and nonlinearities in AUV system are efficiently handled. Then, a data-based predictive control law is further devised, and thereby the dynamics of the entire closed-loop AUV system can be appropriately regulated. Finally, numerical simulations pertaining to an underwater vehicle is given to validate the efficiency of the devised method.