Adaptive Estimation of Aircraft Flight Parameters for Engine Health Monitoring System

Abstract

An adaptive control approach to the implementation of on-line estimation of aircraft flight parameters for the engine health monitoring system is presented. The adaptive estimation system enables a fast reliable data prediction to replicate the missing or misleading data caused by malfunctions in the sensors or communication links, thereby compensating for the deficiency of data that can trigger fault diagnoses of engine health. The estimation method features the integration of an autoregression model and a self-tuning adaptation algorithm for one-step-ahead estimation, in which the manufacturer's baseline values are used as an input in conjunction with an adaptive input adjusted to minimize the estimate error deviated from the snapshot data taken from satellites. The entire system is implemented through the parameter identification and optimization in an attempt to minimize the estimate error. Stability of this adaptive estimation system is investigated, and discrete-time simulations of in-flight parameter estimation will also be presented to show the effectiveness of the present approach