NDLI: Frequency domain global optimization algorithm for the aircraft flutter model parameter identification

Content Provider	IEEE Xplore Digital Library
Author	Jianhong Wang Daobo Wang Zhisheng Wang
Copyright Year	2010
Description	Author affiliation: College of Automation Engineer, Nanjing university of Aeronautics and Astronautics, 210016, China (Jianhong Wang; Daobo Wang; Zhisheng Wang)
Abstract	For stochastic models with input and output measurement noises in aircraft flutter experiment, the maximum likelihood cost function's simple form is firstly proposed by means of frequency domain maximum likelihood estimation principle. Then a global optimization iterative convolution smoothing identification method is derived to significantly reduce the possibility of convergence to a local minimum and weakly dependent of the starting values' choice by using the global optimization theory. The identification method modifies the iterative method with a stochastic perturbation term and guarantees the algorithm converge to a global minimum. The simulation with real flight test data shows the efficiency of the algorithm.
Starting Page	3340
Ending Page	3344
File Size	312077
Page Count	5
File Format	PDF
ISBN	9781424451814
DOI	10.1109/CCDC.2010.5498601
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Frequency domain Maximum likelihood estimation Parameter estimation Optimization methods Convolution smoothing Frequency measurement Noise measurement Parameter identification Frequency domain analysis Global optimization Stochastic resonance Iterative algorithms Maximum likelihood Iterative methods Aircraft
Content Type	Text
Resource Type	Article

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