Aircraft landing control based on fuzzy modeling networks

Aircraft landing control based on fuzzy modeling networks are presented. The proposed scheme uses a fuzzy controller combined with a linearized inverse aircraft model. A multi-layered fuzzy neural network is used as the controller, it provides the control signals in each stage of the aircraft landing phase. The algorithm used to train the network is the back:propagation through time. The linearized inverse aircraft model provides the error signals which will be used to back propagate through the controller in each stage. The objective of this study is to improve the performance of conventional automatic landing systems. The simulation results are described for the automatic landing system of a commercial airplane. Tracking performance and robustness are demonstrated through software simulations. Simulation results show that the fuzzy controller can successfully expand the safety envelope to include more hostile environments such as severe turbulence.