Different types of neural networks (NNs) are surveyed and their suitability as elements in flight control and flight management systems is analyzed. Advantages of neural networks over conventional digital avionic systems include speed (especially when implemented in special hardware, taking advantage of massive parallel processing), robustness, fault tolerance, and the ability to adapt to new situations by learning. An example shows how an artificial NN can be used as a gain adjuster in a stability augmentation system. A three-layer NN receives elevator commands and the sensed resulting longitudinal aircraft motion as input. The NN recognizes certain patterns in this response which are an indication that the gain is too high and that the control system is dangerously close to the stability boundary. Another example shows how a NN can solve a complex combinatorial problem which arises in search planning. It has similarities to the traveling salesman problem.
Artificial neural networks in flight control and flight management systems
Künstliche Nervensysteme in Flugregelungs- und Flugmanagementsystemen
1990
7 Seiten, 7 Quellen
Conference paper
English
Longitudinal Flight Control Decoupling Using Artificial Neural Networks
British Library Conference Proceedings | 1994
|Longitudinal Flight Control Decoupling Using Artificial Neural Networks
British Library Conference Proceedings | 1994
|Neural Networks for Flight Control
NTIS | 1996
|Neural Networks for Flight Control
British Library Conference Proceedings | 1996
|