# Study of Motion Control and a Virtual Reality System for Autonomous Underwater Vehicles
## 1 Introduction  
AUV is a tightly coupled system which has to cope with high nonlinearity, uncertain motion, and severe disturbances. These requirements of the system lead to great challenges for motion control in AUVs. AUVs are used to perform a variety of tasks such as the detection of submarine oil pipeline and cables, the exploration of landform and landscape, the marine observation and analysis of sea level, as well as military application. In all these tasks, an AUV must track specific curves efficiently and accurately. Therefore, motion control is an important technology requirement for AUV research. Presently, researchers worldwide are actively developing AUV control algorithms. Frequently-used AUV control methods are: PID control, sliding mode control, adaptive control, back-stepping method, neural network control, and fuzzy control, and among others. For AUV navigation in a complex marine environment, interference factors such as ocean currents and sea waves vary at different working sea areas and depths. Apart from the maneuverability of the robotic motion, AUV navigation needs to also consider factors such as anti-swinging, stability, and sea-keeping analysis. However, in the complex environment of an ocean, directly using an AUV for experiments not only has high economic costs, but also presents a high risk. Various uncertain factors may easily result in the exposure of experimental devices to perilous environments. This can affect the security of the device and even lead to possible damages to the AUV during experiments. To tackle these challenges, the virtual AUV motion control platform has become a key topic in AUV research. The path and trajectory tracking control of AUV are generally divided into two levels: kinematics and dynamics. Based on the line of sight method (LOS) and vector field method (VF) guiding law, a path tracking controller for underactuated vehicle is designed in literature [1, 2]. A nonlinear backstepping technique based on virtual control variables is employed to design the kinematics and dynamics controllers for the three-dimensional trajectory tracking control of an underactuated autonomous underwater vehicle withunknown current disturbances [3]. However, when there are disturbances such as ocean current, path tracking based on traditional LOS and VF guiding laws will produce steady-state errors. In order to solve this problem, a guiding law of integrated line of sight method (ILOS) was proposed in the literature [4], which has been widely used. There has also been a lot of research on the design of path-following dynamic controllers for underactuated AUVs. Literature [5] applied the ILOS guidance law and PID controller to realize the horizontal path tracking control of underactuated AUV under ocean current disturbance. Literature [6] designed an adaptive controller and a sliding mode controller for the horizontal plane and vertical plane path tracking, respectively. The above literatures only consider the path tracking problem of AUV in the horizontal plane or vertical plane. Literature [7] applied linear stability theory and backstepping method to design a three-dimensional trajectory tracking controller for underactuated AUV. However, the influence of ocean current is not considered in the above 3D path tracking controllers. Since AUV itself has characteristics of uncertainty and non-linearity, coupled with the interference of ocean current, it becomes very difficult to design such a controller. The purpose of path tracking is to reduce the state error of a robot. There are several problems that must be solved; among them, the most difficult and challenging are the highly nonlinear dynamics of the AUV and the uncertainty of the underwater dynamic parameters. The traditional control hardly avoids the problems, such as difficult adjustment of controller parameters, and the robustness.