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Open Loop Morphing Wing Architecture based ANFIS Controller

机译:基于开环变形翼架构的ANFIS控制器

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摘要

To optimize the aerodynamic performance of the aircraft, its wing design is considered as one of the promising approaches. Unlike the conventional control surface technologies such as flaps, variable wing sweep and spoilers, where the wings' structures are changed for different flight conditions, the morphing wing technology has been introduced as another potential approach. In this technology, the aircraft wing surfaces' shape are changed to adapt to flight conditions by using four electrical actuators. They are attached inside the wing to adjust its upper surface's shape, so that the transition point between laminar and turbulent zone is moved closer to the trailing edge of the wing. An adaptive neuro-fuzzy inference system, which is a combination of fuzzy, neural network and adaptive controls, is applied for controlling these actuators. The proposed control method takes advantage of the fuzzy inference system and the self-learning abilities of the neural networks, and of the adaptive control. The experimental and simulation results are obtained using Maxon drives, National Instrument (NI) Veristand and MATLAB/Simulink software. The results show a promising idea of applying artificial intelligent control methods in improving performance of electronic devices and morphing wing technology.
机译:为了优化飞机的空气动力学性能,其机翼设计被认为是有前途的方法之一。与传统的操纵面技术(如襟翼,可变机翼后掠和扰流板)不同,在这种情况下,机翼的结构会因不同的飞行条件而改变,变形翼技术已被引入作为另一种可能的方法。在这项技术中,通过使用四个电动执行器来改变飞机机翼表面的形状以适应飞行条件。它们固定在机翼内部以调整其上表面的形状,从而使层流和湍流区之间的过渡点移近机翼的后缘。将模糊,神经网络和自适应控制相结合的自适应神经模糊推理系统用于控制这些执行器。所提出的控制方法利用了模糊推理系统和神经网络的自学习能力以及自适应控制的优势。使用Maxon驱动器,National Instrument(NI)Veristand和MATLAB / Simulink软件可获得实验和仿真结果。结果表明,应用人工智能控制方法改善电子设备和变形机翼技术的性能具有广阔的前景。

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