Nonlinear parametric system identification using hard excitations

Abdraouf Abusoua, Mohammed Daqaq

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper presents a new approach for the parametric identification of nonlinear systems. The approach is based on subjecting a nonlinear system to a strong high-frequency excitation and monitoring its influence on the slow modulation of the system's response which occurs near its natural frequency. The identification procedure is outlined and numerically implemented on a Duffing-type system with unknown quadratic and cubic nonlinearities. The proposed technique is then implemented to identify the nonlinear parameters of three different experimental systems. Results demonstrate that the proposed approach predicts the nonlinear parameters with good accuracy.

    Original languageEnglish (US)
    Title of host publicationModeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting
    PublisherAmerican Society of Mechanical Engineers
    Volume2
    ISBN (Electronic)9780791850497
    DOIs
    StatePublished - Jan 1 2016
    EventASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016 - Stowe, United States
    Duration: Sep 28 2016Sep 30 2016

    Other

    OtherASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016
    CountryUnited States
    CityStowe
    Period9/28/169/30/16

    Fingerprint

    Nonlinear systems
    Identification (control systems)
    Natural frequencies
    Modulation
    Monitoring

    ASJC Scopus subject areas

    • Building and Construction
    • Civil and Structural Engineering
    • Control and Systems Engineering
    • Mechanics of Materials

    Cite this

    Abusoua, A., & Daqaq, M. (2016). Nonlinear parametric system identification using hard excitations. In Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting (Vol. 2). [V002T03A007] American Society of Mechanical Engineers. https://doi.org/10.1115/SMASIS2016-9075

    Nonlinear parametric system identification using hard excitations. / Abusoua, Abdraouf; Daqaq, Mohammed.

    Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting. Vol. 2 American Society of Mechanical Engineers, 2016. V002T03A007.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abusoua, A & Daqaq, M 2016, Nonlinear parametric system identification using hard excitations. in Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting. vol. 2, V002T03A007, American Society of Mechanical Engineers, ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016, Stowe, United States, 9/28/16. https://doi.org/10.1115/SMASIS2016-9075
    Abusoua A, Daqaq M. Nonlinear parametric system identification using hard excitations. In Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting. Vol. 2. American Society of Mechanical Engineers. 2016. V002T03A007 https://doi.org/10.1115/SMASIS2016-9075
    Abusoua, Abdraouf ; Daqaq, Mohammed. / Nonlinear parametric system identification using hard excitations. Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting. Vol. 2 American Society of Mechanical Engineers, 2016.
    @inproceedings{8048647ba65b4b1996c2641f789f853b,
    title = "Nonlinear parametric system identification using hard excitations",
    abstract = "This paper presents a new approach for the parametric identification of nonlinear systems. The approach is based on subjecting a nonlinear system to a strong high-frequency excitation and monitoring its influence on the slow modulation of the system's response which occurs near its natural frequency. The identification procedure is outlined and numerically implemented on a Duffing-type system with unknown quadratic and cubic nonlinearities. The proposed technique is then implemented to identify the nonlinear parameters of three different experimental systems. Results demonstrate that the proposed approach predicts the nonlinear parameters with good accuracy.",
    author = "Abdraouf Abusoua and Mohammed Daqaq",
    year = "2016",
    month = "1",
    day = "1",
    doi = "10.1115/SMASIS2016-9075",
    language = "English (US)",
    volume = "2",
    booktitle = "Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting",
    publisher = "American Society of Mechanical Engineers",

    }

    TY - GEN

    T1 - Nonlinear parametric system identification using hard excitations

    AU - Abusoua, Abdraouf

    AU - Daqaq, Mohammed

    PY - 2016/1/1

    Y1 - 2016/1/1

    N2 - This paper presents a new approach for the parametric identification of nonlinear systems. The approach is based on subjecting a nonlinear system to a strong high-frequency excitation and monitoring its influence on the slow modulation of the system's response which occurs near its natural frequency. The identification procedure is outlined and numerically implemented on a Duffing-type system with unknown quadratic and cubic nonlinearities. The proposed technique is then implemented to identify the nonlinear parameters of three different experimental systems. Results demonstrate that the proposed approach predicts the nonlinear parameters with good accuracy.

    AB - This paper presents a new approach for the parametric identification of nonlinear systems. The approach is based on subjecting a nonlinear system to a strong high-frequency excitation and monitoring its influence on the slow modulation of the system's response which occurs near its natural frequency. The identification procedure is outlined and numerically implemented on a Duffing-type system with unknown quadratic and cubic nonlinearities. The proposed technique is then implemented to identify the nonlinear parameters of three different experimental systems. Results demonstrate that the proposed approach predicts the nonlinear parameters with good accuracy.

    UR - http://www.scopus.com/inward/record.url?scp=85013968465&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=85013968465&partnerID=8YFLogxK

    U2 - 10.1115/SMASIS2016-9075

    DO - 10.1115/SMASIS2016-9075

    M3 - Conference contribution

    VL - 2

    BT - Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting

    PB - American Society of Mechanical Engineers

    ER -