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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Guo Jin,DONG Yan-liang,ZHAO Ke-ding,GUO Zhi-fu.Model identification of hydraulic flight simulator based on improved particle swarm optimization and wavelet analysis[J].Journal of Harbin Institute Of Technology(New Series),2009,16(5):656-660.DOI:10.11916/j.issn.1005-9113.2009.05.012.
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Model identification of hydraulic flight simulator based on improved particle swarm optimization and wavelet analysis
Author NameAffiliation
Guo Jin College of Mechanical and Electronic Engineering,Harbin Institute of Technology,Harbin 150001,China 
DONG Yan-liang College of Mechanical and Electronic Engineering,Harbin Institute of Technology,Harbin 150001,China 
ZHAO Ke-ding College of Mechanical and Electronic Engineering,Harbin Institute of Technology,Harbin 150001,China 
GUO Zhi-fu College of Mechanical and Electronic Engineering,Harbin Institute of Technology,Harbin 150001,China 
Abstract:
A new model identification method of hydraulic flight simulator adopting improved particle swarm optimization (PSO) and wavelet analysis is proposed for achieving higher identification precision.Input-output data of hydraulic flight simulator were decomposed by wavelet multiresolution to get the information of different frequency bands.The reconstructed input-output data were used to build the model of hydraulic flight simulator with improved particle swarm optimization with mutation (IPSOM) to avoid the premature convergence of traditional optimization techniques effectively.Simulation results show that the proposed method is more precise than traditional system identification methods in operating frequency bands because of the consideration of design index of control system for identification.
Key words:  hydraulic flight simulator  wavelet analysis  multiresolution analysis (MRA)  particle swarm optimization (PSO)  frequency bands weighting approach
DOI:10.11916/j.issn.1005-9113.2009.05.012
Clc Number:V249.4
Fund:

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