AirFlow Angle Estimation Method for Large Passenger Aircraft Based on GA-BP Neural Network
In order to solve the common cause fault of airflow Angle sensor which is difficult to overcome by hard-ware redundancy and further improve the reliability of aircraft air flow Angle signal,an air flow Angle estimation meth-od based on GA-BP neural network was studied.BP neural network was used to integrate attitude Angle,accelera-tion,wind speed and other parameters to estimate the flow Angle independently of the flow Angle sensor.Genetic algo-rithm was introduced to optimize the weights and thresholds of neural network globally to improve the estimation accu-racy.The model was trained and tested with the pre-processed flight test data of a large aircraft.The simulation re-sults show that the trained GA-BP neural network model's estimation of the airflow angle is close to the actual value,and the stability and estimation accuracy are significantly higher than those of the BP neural network.This method adds a residual air flow Angle signal to the aircraft,which can be used to provide reliable air flow Angle signal for the aircraft when the sensor is faulty.
Estimation of flow angleNeural networkGenetic algorithm(GA)Flight test data preprocessingLarge passenger aircraft
NETL
NSTL
万方数据
维普
