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2019 | OriginalPaper | Buchkapitel

EM-Based Online Identification Algorithm for Linear Aerodynamic Model Parameters

verfasst von : Hang Zou, Wei Zhang, Junyi Zuo, Xiaodan Chen, Yawen Cao

Erschienen in: The Proceedings of the 2018 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2018)

Verlag: Springer Singapore

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Abstract

A new algorithm based on expectation maximization (EM) is presented for identifying the parameters and noise covariance matrices in an aircraft dynamic system. The proposed algorithm contains two steps. The first step is to estimate the state of the system using the Kalman filtering (KF) and the current estimator of these unknows. In the second step, the parameters as well as the noise covariance matrices are recursively updated by using the online EM algorithm and the multidimensional stochastic approximation strategy. In order to make a comprehensive comparison of the proposed algorithm and the traditional algorithm, the proposed algorithm is tested by using simulation data and shows desirable estimation accuracy.

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Metadaten
Titel
EM-Based Online Identification Algorithm for Linear Aerodynamic Model Parameters
verfasst von
Hang Zou
Wei Zhang
Junyi Zuo
Xiaodan Chen
Yawen Cao
Copyright-Jahr
2019
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-13-3305-7_182

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