A high efficiency aircraft anti-skid brake control with runway identification

Anti-skid brake system is an important aircraft subsystem to ensure safe take-off and landing of aircraft. Accurate runway circumstances identification is the key point to achieve the high efficiency of the anti-skid brake control. Inaccurate identification may cause frequent skidding and longer brake distance, even cause the extremely dangerous wheel lock phenomenon. Moreover, many nonlinear factors such as the variation of the aerodynamic drag can seriously affect the brake efficiency and the aircraft safety. In this paper, we propose an anti-skid brake control algorithm to identify the maximum friction force by analyzing the runway/tire friction characteristics that can only based on the aircraft wheel speed signal. The aerodynamic disturbances are observed and compensated by radical basis function (RBF) neural network, and the brake disc friction coefficient variation is also estimated based on the observation of energy consumption. Software simulations and the inertial test bench experiments are carried out. The result reveals that this method can accurately identify the runway circumstances and greatly improve the braking efficiency.