Automatic Control of an Asymmetric Fighter Aircraft Performing Supermanoeuvres

Abstract

Centre-of-gravity (c.g.) of combat aircraft suffers significant lateral deviation due to asymmetric release of stores, leading to a highly nonlinear and coupled dynamics. Additional nonlinearity and coupling result when the aircraft attempts some supermanoeuvres under such conditions rendering nonlinear control implementation unavoidable. However, such controls depend on accurate onboard c.g information. The present paper proposes a novel neural network aided sliding mode based hybrid control scheme which does not require such an information. The neural controller is trained offline to compensate for the changed dynamics arising from the lateral mass asymmetry, while the sliding controller is designed for the intended manoeuvres under the nominal situation. Cobra and Herbst manoeuvres are simulated for various lateral c.g. movements to validate the scheme.