A neural network based heading and position control system of a ship

  • Shahroz Unar The Institute of Information & Communication Technologies, Mehran University of Engineering & Technology, Jamshoro Pakistan
  • Mukhtiar Ali Unar Department of Computer Systems Engineering, Mehran University of Engineering and Technology, Jamshoro Pakistan
  • Zubair Ahmed Memon Department of Electrical Engineering, Mehran University of Engineering and Technology, Jamshoro Pakistan
  • Sanam Narejo Department of Computer Systems Engineering, Mehran University of Engineering and Technology, Jamshoro Pakistan

Abstract

Heading and position control system of ships has remained a challenging control problem. It is a nonlinear multiple input multiple output system. Moreover, the dynamics of the system vary with operating as well as environmental conditions. Conventionally, simple Proportional Integral Derivative controller is used which has well known limitations. Other conventional control techniques have also been investigated but they require an accurate mathematical model of a ship. Unfortunately, accuracy of mathematical models is very difficult to achieve. During the past few decades computational intelligence techniques such as artificial neural networks have been very successful when an accurate mathematical model is not available. Therefore, in this paper, an artificial neural network controller is proposed for heading and position control system. For simulation purposes, a mathematical model with four effective thrusters have been chosen to test the performance of the proposed controller. The final closed loop system has been analysed and tested through simulation studies. The results are very encouraging.

Published
Apr 1, 2022
How to Cite
UNAR, Shahroz et al. A neural network based heading and position control system of a ship. Mehran University Research Journal of Engineering and Technology, [S.l.], v. 41, n. 2, p. 172-177, apr. 2022. ISSN 2413-7219. Available at: <https://publications.muet.edu.pk/index.php/muetrj/article/view/2447>. Date accessed: 17 may 2022. doi: http://dx.doi.org/10.22581/muet1982.2202.16.
Section
Articles
This is an open Access Article published by Mehran University of Engineering and Technolgy, Jamshoro under CCBY 4.0 International License