This paper proposes a robust H 2 optimal control strategy for the depth-plane motion of an
autonomous underwater vehicle (AUV) in the presence of output disturbances and time …

In this article, we propose a robust depth control design scheme for autonomous underwater
vehicles (AUVs) in the presence of hydrodynamic parameter uncertainties and disturbances …

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 …

Large fluctuation, large overshoot, and uncertain external disturbance that occur when an
autonomous underwater vehicle is in deep motion are difficult to address using the …

In order to simplify the design of path tracking controller and solve the problem relating to
nonlinear dynamic model of autonomous underwater vehicle motion planning, feedback …

This work renders the design of a robust state feedback optimal control strategy for an
Autonomous Underwater Robotic Vehicle (AURV). The control strategy is developed using a …

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

This paper proposes a new robust nonlinear H _ ∞ H∞ state feedback (NHSF) controller for
an autonomous underwater vehicle (AUV) in steering plane. A three-degree-of-freedom …

A conventional region control technique cannot meet the demands for an accurate tracking
performance in view of its inability to accommodate highly nonlinear system dynamics …

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 …