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- W2053103650 abstract "Anonlinearadaptivee ightcontrol system isproposed using a backstepping and neural networks controller. The backstepping controlleris used to stabilize allstatevariablessimultaneously withoutthetwo-timescaleassumption that separatesthefastdynamics,involving theangularratesoftheaircraft,from theslowdynamics,whichincludes angle of attack, sideslip angle, and bank angle. It is assumed that the aerodynamic coefe cientsinclude uncertainty, and an adaptive controller based on neural networks is used to compensate for the effect of the aerodynamic modeling error. Under mild assumptions on the aerodynamic uncertainties and nonlinearities, it is shown by the Lyapunov stability theorem that the tracking errors and the weights of neural networks exponentially converge to a compactset. Finally, nonlinearsix-degree-of-freedom simulation resultsfor an F-16 aircraft model are presented to demonstrate the effectiveness of the proposed control law. Nomenclature F = aerodynamic force about the body-e xed frame I = moment of inertia L; M; N = aerodynamic rolling, pitching, yawing moment p;q;r = roll, pitch, yaw rate about the body-e xed frame N q = dynamic pressure T = thrust V = velocity ®;¯ = angle of attack, sideslip angle ±e;±a;±r = elevator, aileron, rudder angle A;µ;A = roll, pitch, yaw angle" @default.
- W2053103650 created "2016-06-24" @default.
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- W2053103650 date "2001-07-01" @default.
- W2053103650 modified "2023-09-30" @default.
- W2053103650 title "Nonlinear Adaptive Flight Control Using Backstepping and Neural Networks Controller" @default.
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- W2053103650 doi "https://doi.org/10.2514/2.4794" @default.
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