Bandwidth self-adaption recognition method for flight dynamic model based on trial flight data

Abstract

The invention discloses a bandwidth self-adaption recognition method for a flight dynamic model based on trial flight data and belongs to the technical field of aircraft flight test and flight dynamic model. The method adopts a translation mechanical action on a window function center, a copy mechanical motion and a zero-filling rounding data pretreatment technique, so as to reduce the reduction effect of window function edge and increase the precision of a frequency domain recognition result. A classical Welch spectrum estimation method is adopted for calculating input and output power spectral density, coherence function and frequency domain response and a multi-window synthesis technique is adopted for further increasing the precision of the frequency domain recognition result. A low-order equivalent flight dynamical model and an equivalent analog-matching frequency count are selected; a frequency width scope and a frequency node position for parameterized model recognition are self-adaptively confirmed according to the coherence function and the power spectral density; the least square method frequency domain low-order equivalent fitting is optimized, so that a more accurate parameterized low-order equivalent model is acquired.

Description

technical field [0001] The invention relates to a flight dynamics model bandwidth adaptive identification method based on flight test data, in particular to an identification method for low signal-to-noise ratio short-term maneuver flight test data, and belongs to the technical field of aircraft flight test and flight dynamics model identification. Background technique [0002] After the flight dynamics system identification is carried out on the flight test data under the specific input of the aircraft, supporting data for system modeling, wind tunnel test data calibration, flight control system design and flight quality evaluation can be obtained. An important work in engineering. Because the flight test is affected by many factors such as the type of input excitation signal, the accuracy of the measurement equipment, system interference, and flight atmospheric environment, it is very difficult to accurately identify the aircraft dynamic model from the flight test data. I...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of the existing frequency-domain identification method based on flight test data, which have strict requirements on long-term sweep input excitation and low accuracy of identification results such as short-time pulses and double pulses, the present invention provides a flight dynamics model based on flight test data. wide adaptive identification method

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