K. Krishnakumar et al., NEURO-CONTROLLERS FOR ADAPTIVE HELICOPTER HOVER TRAINING, IEEE transactions on systems, man, and cybernetics, 24(8), 1994, pp. 1142-1152
Citations number
6
Categorie Soggetti
Controlo Theory & Cybernetics","Computer Science Cybernetics","Engineering, Eletrical & Electronic
This paper presents an application of artificial neural networks in ad
aptive helicopter hover training of novice student pilots. The design
of the adaptive trainer utilizes the hypothesis that novices can be tr
ained to fly a helicopter system automatically (with no human interact
ion) if the helicopter system adapts to the learning curve of the stud
ent. Two different techniques based on the above approach are presente
d. In the first technique, the helicopter system actively enforces opt
imality by augmenting the novice's control inputs by amounts necessary
to satisfy desired performance criteria. The second technique uses re
laxed performance criteria that are not initially optimal, but approac
h optimality in a graded fashion, based on the learning curve of the s
tudent. Adaptive neuro-controllers, together with a critic model, are
used to implement the adaptive helicopter system. The results using si
mulated student models verify the approach adopted, and show that the
adaptive neuro-controllers allow the helicopter system to adapt to the
novice's learning curve.