We consider the problem of gray-box identification of dynamic models for mechanical systems. In particular, the problem is approached by means of continuous-time system identification using subspace-based methods based on discrete-time input-output identification data. A method is developed, with the property that the structure of the model resulting from fundamental physical first principles is obtained and the parameter matrices have a clear physical interpretation. The proposed method is subsequently successfully validated in both simulation and using experimental data from a micro manipulator. In both cases the identified models exhibit good fit to the input-output data. The results indicate that the proposed method can be useful in the context of model-based control design in, for example, impedance force control for robots and manipulators, but also for modal analysis of mechanical systems.


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    Title :

    Continuous-Time Gray-Box Identification of Mechanical Systems Using Subspace-Based Identification Methods


    Contributors:

    Publication date :

    2014-01-01


    Remarks:

    pp 327-333 (2014) ; ISSN: 2159-6255


    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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