Ship Steering Control Based on Quantum Neural Network

Neural Network Based Model Reference Adaptive Control for Ship Steering System

A neural network-based model reference adaptive control approach (MRAC) for ship steering systems is proposed in this paper. For the nonlinearities of ship steering system, performances of traditional adaptive control algorithms are not satisfactory in fact. The presented MRAC system utilizes RBF neural network to approximate the unknown nonlinearities in order to get a high adaptive control pe...

Ontology-based fuzzy support agent for ship steering control

The important field of research on ship operation is related to the high efficiency of transportation, the convenience of maneuvering ships, and the safety of navigation. This paper proposes an ontology-based fuzzy support agent for ship steering control and desires to testify the validity of the proposal by applying the fuzzy control model to the steering control system based on linguistic ins...

Hybrid Intelligent Control for Ship Steering

This paper is concerned with the application of hybrid intelligent control techniques for improving the performance of ship steering. Hybrid intelligent controllers can make full use of the advantages of a variety of intelligent algorithms. In this paper, optimization with genetic algorithms is used in off-line learning periods and reinforcement learning and neural fuzzy control are integrated ...

Ship Steering

Course Control of Underactuated Ship Based on Nonlinear Robust Neural Network Backstepping Method

The problem of course control for underactuated surface ship is addressed in this paper. Firstly, neural networks are adopted to determine the parameters of the unknown part of ideal virtual backstepping control, even the weight values of neural network are updated by adaptive technique. Then uniform stability for the convergence of course tracking errors has been proven through Lyapunov stabil...