A Neural Network Controller for Suppression of Wing Rock

J. Chandrasekhar and A.G. Sreenatha (Australia)


Wing rock, ANN, Fighter Aircraft,Rule Base, Feedforward


Artificial Neural Networks (ANNs) are known to be effective in controlling behaviour of non-linear and uncertain systems. Wing rock is one such highly non linear aerodynamic phenomenon seen, at high angles of attack, in fighter-class of aircraft with swept back wings. The dynamic motion manifests itself as a limit cycle roll oscillation. The paper presents the design of a feedforward neural network to suppress wing rock. Data for training the neural network are generated using experiments carried out in the wind tunnel on a slender delta wing model. Numerical results, based upon simulations on an approximate mathematical model of the phenomenon, show the effectiveness of the controller in suppressing the wing rock.

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