Adaptive flying path prediction method of aircraft auto ground collision avoidance system

Abstract

The invention discloses an adaptive flying path prediction method of an aircraft automatic near-field collision avoidance system. The method comprises following steps of A, collecting flying state andposition information data from a flight management system, and taking the collected information as state input of step B; B, resolving the state input according to a maneuver avoidance basic controllaw so as to obtain basic output; C, delivering compensation output for unmodeled dynamic uncertainty of an aircraft model and external interference approximation by using an interference observer based on a functional neural network, assisting controlling by using an RC link with robustness gain adaptively regulated so as to obtain compensation output; and D, using a sum of outputs of step B andC as input of a flight model, and resolving state and position information of step i. The method establishes a more complete state equation, improves flying path prediction accuracy, lowers Auto-GCASfalse alarm rate, makes Auto-GCAS more effective, and combines with the flight management system, flight control system and other avionics systems, thereby effectively guaranteeing flight security ofaircrafts.

Description

technical field [0001] The present invention relates to the field of aviation control technology, especially an adaptive flight trajectory prediction technology involved in the automatic ground proximity avoidance system used in aviation, such systems include but not limited to automatic ground proximity avoidance system, ground proximity warning System, terrain warning and warning system and other specific products. Background technique [0002] The Auto Ground Collision Avoidance System (Auto-GCAS) is an avionics system that improves aircraft flight safety and reduces Controlled Flight Into Terrain (CFIT) accidents. Its core is to calculate and predict the flight trajectory of the aircraft in real time based on the dynamic characteristics of the aircraft and according to the current state information of the aircraft; use the airborne digital terrain data, and according to the flight trajectory of the aircraft, calculate the predicted trajectory in real time through the ter...

AI Technical Summary

Problems solved by technology

[0005] However, in the process of flight trajectory prediction and calculation, due to the cumulative error of nonlinear equation solution, unmodeled dynamic uncertainty and external disturbance torque, atmospheric environment (wind shear, turbulence) and other factors are all factors when establishing a flight model. Problems that need to be solved but cannot be completely solved, which will directly affect the trajectory prediction accuracy

Images