The Deep Reinforcement Learning (DRL) algorithm is an optimal control method with
generalization capacity for complex nonlinear coupled systems. However, the DRL agent …

Due to the growing interest using model predictive control (MPC), there are more and more
researches about the applications of MPC on autonomous underwater vehicle (AUV), and …

This paper addresses the region tracking control problem for an autonomous underwater
vehicle (AUV) and proposes a prediction-based region tracking control (PRTC) scheme for …

Abstract This paper adopts Deep Deterministic Policy Gradient (DDPG) algorithm in Deep
Reinforcement Learning (DRL) to analyse the eca_a9 Autonomous Underwater Vehicle …

An uncertain ocean environment demands robust control to manoeuvre autonomous
underwater vehicle (AUV) to achieve the control objectives. The desired depth of the vehicle …

This paper presents an experimental analysis of a nonlinear model predictive controller
combined with an integral sliding mode control component and an explicit dead-time …

The underwater vehicle-manipulator (UVM) interaction tasks require that UVM can adapt to
different environments and have good stability properties. However, the complicated …

This paper presents a study of depth tracking controller design for a hybrid AUV in the
presence of model uncertainty and propeller torque's effect. Firstly, the six degrees of …

A robust model predictive controller (RMPC) based on the H∞ criterion is proposed for
accomplishing effective path following motion plan of an Autonomous Underwater Vehicle …

Aiming at the difficult problem of motion control of under-actuated and X-rudder autonomous
underwater vehicle (AUV), the present work adopts deep reinforcement learning (DRL) …