Analysis of Fuzzy Neural Network Control Applied to the Lateral Maneuvering of Aircraft

Abstract

It is reported that a control augmentation system (CAS) with a fuzzy neural network (FNN) controller for an aircraft is robust against various flight conditions. This paper describes the evaluation of the optimality of the FNN learning results based on the internal structure of the FNN control unit, and the simulation results of its control performance. We conclude that internal structure of the FNN control unit is approximately composed of gain and offset and that the gain and the offset obtained by the learning FNN can reduce the learning error to 0, i.e. FNN carries out the optimal learning. Furthermore, we have confirmed that if the rate of the aileron and the rudder may saturate, the controller composed of the gain and the offset obtained by the FNN is more robust than apply the FNN controller directly.