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UAV Adaptive Control Laws Using Non-Linear Dynamic Inversion Augmented with an Immunity-based Mechanism

机译:带有基于抗扰度机制的非线性动态反演的无人机自适应控制律

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In this paper, a novel adaptive flight control system is presented, designed to handle failures and malfunctions of aircraft sub-systems as well as general environmental upset conditions. The proposed control laws use a non-linear dynamic inversion approach augmented with an artificial immune system mechanism that relies on a direct compensation inspired primarily by the biological immune system response. This work is an extension of a recently developed artificial immune system-based architecture which implements negative and positive selection algorithms for aircraft fault detection, identification, and evaluation within a hierarchical multi-self scheme. The effectiveness of the approach is demonstrated through simulation examples within the West Virginia University unmanned aerial vehicle simulation environment. The performance of the control laws is evaluated in terms of trajectory tracking errors and control activity during autonomous flight in the presence of atmospheric disturbances and actuator failures. The results show that the proposed fault tolerant adaptive control laws significantly improve the tracking performance of the vehicle at nominal conditions and under a variety of abnormal flight conditions.
机译:在本文中,提出了一种新颖的自适应飞行控制系统,旨在处理飞机子系统的故障和失灵以及一般的环境不正常状况。拟议的控制定律使用非线性动态反演方法,并辅以人工免疫系统机制,该机制依赖于主要受生物免疫系统反应启发的直接补偿。这项工作是对最近开发的基于人工免疫系统的体系结构的扩展,该体系结构在分层多自我方案内实现了用于飞机故障检测,识别和评估的阴性和阳性选择算法。西弗吉尼亚大学无人飞行器仿真环境中的仿真示例证明了该方法的有效性。在大气干扰和执行器故障的情况下,根据自主飞行过程中的轨迹跟踪误差和控制活动来评估控制律的性能。结果表明,所提出的容错自适应控制律显着提高了车辆在正常条件下和各种异常飞行条件下的跟踪性能。

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