Adaptive Variable Structure Control With Neuron for Path Tracking of Beaver AUV

Abstract

In order to improve path tracking performance of Beaver AUV, a new method for path tracking controller design is proposed basing on variable structure control theory and nonlinear dynamics model of Beaver. Switching surface of variable structure controllers is founded with corresponding error and error derivative of surge displacement and yaw angle. Exponential approach law is adopted to derive control algorithm for surge and yaw in the process of path tracking. Chattering phenomenon is restrained due to adaptive neurons which are used for approaching speed adjusting online. Simulation results of sinusoidal path tracking, circular path tracking and planning path tracking show that tracking precision of Beaver AUV is improved more evidently through variable structure control with adaptive approaching speed compared with variable structure control using fixed approaching speed. The method proposed in this article is effective and feasible. INDEX TERMS Autonomous underwater vehicle, neuron, path tracking, variable structure control.

Path-Tracking Control Strategy of Unmanned Vehicle Based on DDPG Algorithm

“…The steering wheel angle of the vehicle obtained by this type of controller is usually related to the heading angle error and lateral error of the vehicle. This method is easy to implement, but it can only achieve the real-time response of the vehicle at low speeds, and is not suitable for tracking control in high-speed conditions [ 1 , 2 ]. When considering complex urban conditions and high-speed traffic environments, the reliability and robustness of the controller of the model are not highly based on kinematics, so a vehicle dynamics model needs to be introduced.…”