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  • 1
    Publication Date: 1997-03-01
    Print ISSN: 0376-0421
    Electronic ISSN: 1873-1724
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Published by Elsevier
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  • 2
    Publication Date: 2005-07-01
    Print ISSN: 1270-9638
    Electronic ISSN: 1626-3219
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Published by Elsevier
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  • 3
    Publication Date: 2019-06-28
    Description: Models of the open-loop hover dynamics of the XV-15 Tilt-Rotor Aircraft are extracted from flight data using two approaches: frequency-domain and time-domain identification. Both approaches are reviewed and the identification results are presented and compared in detail. The extracted models compare favorable, with the differences associated mostly with the inherent weighting of each technique. Step responses are used to show that the predictive capability of the models from both techniques is excellent. Based on the results of this study, the relative strengths and weaknesses of the frequency- and time-domain techniques are summarized, and a proposal for a coordinated parameter identification approach is presented.
    Keywords: AERODYNAMICS
    Type: NASA-TM-89404 , A-86435 , NAS 1.15:89404 , USAAVSCOM-TR-86-A-3
    Format: application/pdf
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  • 4
    Publication Date: 2017-10-02
    Description: Models of the open-loop hover dynamics of the XV-15 Tilt-Rotor Aircraft are extracted from flight data using two approaches: frequency domain and time-domain identification. Both approaches are reviewed and the identification results are presented and compared in detail. The extracted models are compared favorably, with the differences associated mostly with the inherent weighing of each technique. Step responses are used to show that the predictive capability of the models from both techniques is excellent. Based on the results of this study, the relative strengths and weaknesses of the frequency and time-domain techniques are summarized and a proposal for a coordinated parameter identification approach is presented.
    Keywords: AIRCRAFT DESIGN, TESTING AND PERFORMANCE
    Type: AGARD, Rotorcraft Design for Operations; 20 p
    Format: application/pdf
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  • 5
    Publication Date: 2018-12-01
    Description: Mathematical models for the dynamics of the DLR BO 105 helicopter are extracted from flight test data using two different approaches: frequency-domain and time-domain identification. Both approaches are reviewed. Results from an extensive data consistency analysis are given. Identifications for 6 degrees of freedom (DOF) rigid body models are presented and compared in detail. The extracted models compare favorably and their prediction capability is demonstrated in verification results. Approaches to extend the 6 DOF models are addressed and first results are presented. System identification is broadly defined as the deduction of system characteristics from measured data. It provides the only possibility to extract both non-parametric (e.g., frequency responses) and parametric (e.g., state space matrices) aircraft models from flight test data and therefore gives a reliable characterization of the dynamics of the actually existing aircraft. Main applications of system identification are seen in areas where higher accuracies of the mathematical models are required: Simulation validation, control system design (in particular model-following control system design for in-flight simulation), and handling qualities.
    Keywords: AIRCRAFT DESIGN, TESTING AND PERFORMANCE
    Format: text
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  • 6
    Publication Date: 2019-07-13
    Description: Mathematical models for the dynamics of the DLR BO 105 helicopter are extracted from flight test data using two different approaches: frequency-domain and time-domain identification. Both approaches are reviewed. Results from an extensive data consistency analysis are given. Identifications for 6 degrees of freedom (DOF) rigid body models are presented and compared in detail. The extracted models compare favorably and their prediction capability is demonstrated in verification results. Approaches to extend the 6 DOF models are addressed and first results are presented. System identification is broadly defined as the deduction of system characteristics from measured data. It provides the only possibility to extract both non-parametric (e.g., frequency responses) and parametric (e.g., state space matrices) aircraft models from flight test data and therefore gives a reliable characterization of the dynamics of the actually existing aircraft. Main applications of system identification are seen in areas where higher accuracies of the mathematical models are required: Simulation validation, control system design (in particular model-following control system design for in-flight simulation), and handling qualities.
    Keywords: AIRCRAFT DESIGN, TESTING AND PERFORMANCE
    Type: AD-A216828 , European Rotorcraft Forum; Sep 12, 1989 - Sep 15, 1989; Amsterdam; Netherlands
    Format: text
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