Open loop morphing wing architecture based ANFIS controller

Abstract

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.