Cruise and Operation of a Biomimetic Underwater Vehicle via Parametrization Adaptive Model Predictive Control

Abstract

Motivated by the need to replace the artificial collection of marine organisms, a bionic undulating fin-propelled biomimetic underwater vehicle (BUV) with low-speed stability is developed. A parametrization adaptive model predictive controller (PAMPC) algorithm is proposed for the control of the BUV. Active attitude stability control of roll and pitch angles and various practical constraints, such as the velocity, maximum angles, and control inputs saturation, are fully considered by the PAMPC. To stabilize the system states faster, nonlinear adaptive weight functions are designed for the state errors and the change of state errors, respectively. Furthermore, the change rate of the control inputs is considered in the optimization function to ensure the attitude stability of the BUV. Finally, comparative simulations and experiments between the PAMPC and the traditional MPC, and an experiment of the BUV autonomous depth-fixed cruising and collecting marine organisms with stable attitude angles are carried out to verify the performance.