Flight experiment data rapid frequency domain identification method suitable for a telex flight control helicopter

Abstract

The invention belongs to the field of helicopter model identification, and provides a flight experiment data rapid frequency domain identification method suitable for a telex flight control helicopter, which comprises the following steps of: 1, eliminating and correcting a data outlier, performing low-pass filtering, correcting a sensor position, checking data compatibility and reconstructing data; 2, converting the flight experiment data into a frequency domain, constructing an identification model, and adopting a completely linearized state space model; 3, fast initial value estimation is carried out, and initial value estimation theta of the to-be-identified parameters is obtained; 4, model structure identification is carried out, and before the next step of identification is carried out, the parameters are selected and used; And 5, outputting an error in a fast frequency domain. According to the method, the accelerated optimization algorithm is designed according to the characteristic that the convergence rates of the parameters to be identified are different, so that the calculation efficiency is further improved, the relatively detailed description of the frequency spectrum is realized, and meanwhile, the calculation amount is ensured.

Description

technical field [0001] The invention belongs to the field of helicopter model identification. Background technique [0002] The parameter identification method based on flight test data provides an effective technical means for evaluating the flight quality of helicopters. Both domestic and foreign flight quality standards propose a method to check the flight quality of a helicopter by parameter identification. The so-called parameter identification is to establish a mathematical model of the system based on the input-output data obtained from the flight test. Its main feature is that it does not need to know the detailed physical mechanism details of the research object. However, in order to identify a model that matches the actual situation, it is necessary to generate experimental data that can fully reflect the characteristics of the research object, to establish a parametric model that can reasonably describe the research object, and to have an identification algorithm...

AI Technical Summary

Problems solved by technology

However, due to the inherent complexity of the parametric model of helicopter flight dynamics, including the large number of parameters to be identified, the large sensitivity difference of each parameter under different control inputs, etc., it brings many mathematical problems to the identification of the model. The identification algorithm of accuracy and efficiency becomes the key to the success or failure of the identification of the helicopter flight dynamics model

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