Innovating aircraft control systems with the use of artificial intelligence and electronics

Qasim Abdul-Aziz, Hassan H. Hashemi
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Abstract

Despite all the research being done in an attempt to bridge the gap between control systems and artificial intelligence, there is still an immense risk of failure and instability that exists. One particular application that this research will look into and expand on is aircraft control mechanisms. This article will examine the existing uncertainties within these systems that could be suspected as the cause of failure in the artificial control operation of an aircraft. This study will act as a further extension of research on the feedback linearization of an aircraft's control architecture using adaptive neural networks to decrease the probability of an uncontrolled error resulting from the nonlinearity of the aircraft's dynamic characteristics. The stability of previously implemented mechanisms to control aircraft systems will also be investigated. This research will require a thorough approach and understanding of various possible areas of malfunction and instability caused by multiple factors, including, external interferences and inefficiencies that accumulate within the controller that can mislead or cause an undesirable effect on the system. Examining similar areas where this study may be used for further research, while also discussing opportunities to apply these procedures to relatable applications will be analyzed, as it is of key importance for the progression of this technology.

Abstract Image

利用人工智能和电子技术创新飞机控制系统
尽管所有的研究都在试图弥合控制系统和人工智能之间的差距,但仍然存在巨大的失败和不稳定风险。这项研究将研究和扩展的一个特殊应用是飞机控制机制。本文将研究这些系统中存在的不确定性,这些不确定性可能被怀疑是飞机人工控制操作失败的原因。本研究将作为飞机控制结构反馈线性化研究的进一步扩展,使用自适应神经网络来减少由飞机动态特性非线性引起的不可控误差的概率。还将研究以前实现的控制飞机系统的机制的稳定性。这项研究将需要彻底的方法和理解由多种因素引起的各种可能的故障和不稳定区域,包括外部干扰和控制器内积累的低效率,这些因素可能会误导或对系统造成不良影响。本研究可能用于进一步研究的类似领域,同时也将讨论将这些程序应用于相关应用的机会,因为这对该技术的进步至关重要。
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