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Improved Design and Implementation of Automatic Flight Control System (AFCS) for a Fixed Wing Small UAV

机译:固定翼小型无人机自动飞行控制系统(AFCS)的改进设计和实现

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This paper presents an implementation of automatic flight control system (AFCS); analyzes and assures its performance during model in loop (MIL), software in loop (SIL), and processor in loop (PIL) stages. Based on both linear and analytic linear models with trimmed values of straight and leveling scenario, the proposed autopilot is applied to an Ultrastick-25e fixed wing unmanned aerial vehicle (UAV). The implementation of Ultrastick-25e AFCS is accomplished according to the resulted design parameters, and performing various flight scenarios. The choice of avionics and sensors of small UAV (SUAV) required for stability based on commercial off the Shelf (COTS) components. The proposed design uses low cost and light weight micro electro mechanical systems (MEMS) as new sensor technology. Since MEMS suffers from various types of noise, state estimation technique is introduced using both Kalman filter (KF) and complementary filter. Moreover, both results of KF and complementary filter are compared. Finally, PIL simulation is implemented to evaluate the autopilot as hardware components and software algorithms for management and PID control structure with its parameters proposed for implementing AFCS. The results show a good performance in disturbance rejection and robustness against sensors noise.
机译:本文介绍了自动飞行控制系统(AFCS)的实现;在回路模型(MIL),回路软件(SIL)和回路处理器(PIL)阶段分析并确保其性能。在线性和解析线性模型的基础上,将直线和水准情景的修正值进行修正,将拟议的自动驾驶仪应用于Ultrastick-25e固定翼无人飞行器(UAV)。 Ultrastick-25e AFCS的实现是根据产生的设计参数并执行各种飞行方案完成的。基于商用现货(COTS)组件,选择稳定所需的小型UAV(SUAV)航空电子设备和传感器。拟议的设计使用低成本和轻量的微机电系统(MEMS)作为新的传感器技术。由于MEMS受各种类型的噪声困扰,因此同时使用卡尔曼滤波器(KF)和互补滤波器引入了状态估计技术。此外,比较了KF和互补滤波器的结果。最后,进行PIL仿真以评估自动驾驶仪作为管理和PID控制结构的硬件组件和软件算法,并提出用于实现AFCS的参数。结果显示出良好的抗干扰性能和抗传感器噪声的鲁棒性。

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