Adaptive neuro-fuzzy controllers for an open-loop morphing wing system

Abstract

A new method for the realization of two neuro-fuzzy controllers for a morphing wing design application is presented here. The controllers' main function is to correlate each set of pressure differences, calculated between the optimized and the reference airfoil, with each of the airfoil deformations produced by the actuators' system. The pressures are calculated at different chord positions and will also be measured during wind tunnel tests. During a first identification phase, the two fuzzy inference systems (FISs) from the controllers' structure are generated for 16 flight conditions characterized by Mach numbers and angles of attack. Next, the FIS are optimized with the Matlab function adaptive neuro-fuzzy inference system (ANFIS) by training over different epochs. Finally, the controllers are validated for the other 33 flight conditions of the open-loop morphing wing system. This is the first time that such a method of relating the pressure differences to airfoil displacements has been conceived and used in an open-loop morphing wing controller system.