Application of resource allocating network and particle swarm optimization to ALS

Abstract

This paper presents two intelligent aircraft automatic landing control schemes that use neural network controller and neural controller with particle swarm optimization to improve the performance of conventional automatic landing systems. Control signals of the aircraft are obtained by resource allocating neural networks. Control gains are selected by particle swarm optimization. Simulation results show that the proposed automatic landing controllers can successfully expand the safety envelope of an aircraft to include severe wind disturbance environments without using the conventional gain scheduling technique.