Estimating the sea current and finding the optimal heading of an AUV through neural network motion control

For an autonomous underwater vehicle (AUV), sea current is an unknown varying parameter which can not be given before operation and which may impose significant influence on the performance of an AUV. Furthermore, it is difficult to measure the sea current from a moving or suspending AUV. This paper presents a technique for automatically estimating the sea current and finding the optimal heading through neural network motion control. By using a model reference neural network controller, the velocity vector of the vehicle can be oriented to point to the goal position. Meanwhile the heading of the vehicle turns to the angle where the lateral resistance approaches to zero. When the vehicle reaches the goal point, the heading is approximately opposite to the direction of the current. Thus, the AUV can estimate the direction of the current with little error.