Tracking Control of Underactuated Unmanned Surface Vessels Based on the Dynamic Fuzzy Neural Network

Abstract

This paper proposes a dynamic fuzzy neural network (DFNN) for the tracking control of the underactuated unmanned surface vessels. The dynamic fuzzy neural network control algorithm has the advantages of both fuzzy logical and neural network. The algorithm adjusts the structure and parameters on line at the same time to make the tracking effect of the system being fast and accurate, while it doesn’t need confirm the fuzzy rules and the nodes of hidden layer. The simulation experiments based on the proposed control algorithm are carried out and the simulation results validate its effectiveness.