Neural Predictive Tracking Control of Catamaran Model Sailboat for Situation Awareness Applications

I. Astrov, A. Udal
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引用次数: 1

Abstract

Adding artificial intelligence into the control of autonomous vehicles has become a task of steeply rising importance in development of new transportation systems and cyber-physical systems for different applications like Industry 4.0 systems and attaining Situation Awareness (SA). In contrast to the significant growth in unmanned aerial vehicle research, the study autonomous waterborne craft has remained at a relatively modest level. Paper discusses methodology of model-based modeling and simulation in Simulink/MATLAB software environment of a catamaran sailboat moving under the wind influence. The functioning of catamaran sailboat together with predictive neural network controller has been simulated for movement at the different sailing angles and wind conditions. Results confirm the applicability and good quality of neural predictive control approach.
基于态势感知的双体模型帆船神经预测跟踪控制
在工业4.0系统等不同应用的新交通系统和网络物理系统的开发和实现态势感知(SA)中,将人工智能添加到自动驾驶汽车的控制中已经成为一项重要性急剧上升的任务。与无人机研究的显著增长相比,自主水上飞行器的研究仍然处于相对适度的水平。本文讨论了在Simulink/MATLAB软件环境下双体帆船在风的作用下运动的基于模型的建模与仿真方法。结合预测神经网络控制器对双体帆船在不同航行角度和风向条件下的运动进行了仿真。结果证实了神经预测控制方法的适用性和良好的控制效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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