Computer Simulation Research of Self-adaptive Compensation Control Based on Neural Network for Control Surface Failure of Uncertain Tailless Flying Wing Aircraft

Abstract

The conventional aircraft layout will contain the elevator, aileron, rudder three control surfaces, and thus generate three control moments to adjust the aircraft trajectory and flight attitude. However, the aircraft with multi-control plane flying wing layout needs to choose redundant new control plane configuration, which is quite different from the conventional aircraft layout in both control method and operation mode. Since there are many problems in the aircraft motion mathematical model during the ownership period, which will directly affect the control effect of the flight control system, in order to reduce dynamic error and improve the robustness and accuracy of the flight control system, this paper proposes an adaptive neural network algorithm. Combined with the current operating status of tailless flying wing aircraft and the research status of aircraft control system analysis, this paper mainly discusses the design differences between the adaptive control system and the original control system, based on the empirical case, to clarify the compensation effect of the adaptive control system.