Longitudinal Control for AUV with Self-Adaptive Learning Law

Abstract

A mini AUV (Autonomous Underwater Vehicle) with cross shaped rudders and one single thruster is presented, which features high maneuverability due to the intelligent control algorithm. A single variable PID neural network controller is also proposed, which is utilized to maintain attitude for the vehicle. In order to testify feasibility of the control methodology, a spatial motion mathematic model is constructed and linear equations that indicate the relation between attitude angles of vehicle and deflection angles of rudders is deduced firstly. Subsequently, the neural network PID controller is developed according to the deduced equations and the attitude control simulation of the vehicle with this controller is conducted. Taking actual and desired attitude angles of the vehicle as input and deflection angles of the rudders as output, this controller performs self-adaptive update for 9 synaptic weights through back-propagation algorithm and employs the converged weights to calculate the appropriate deflection angle of each rudder.