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

Autor: Shahroz Unar, Mukhtiar Ali Unar, Zubair Ahmed Memon, Sanam Narejo
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Mehran University Research Journal of Engineering and Technology, Vol 41, Iss 2, Pp 172-177 (2022)
Druh dokumentu: article
ISSN: 0254-7821
2413-7219
DOI: 10.22581/muet1982.2202.16
Popis: 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.
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