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    Repeated eigenstructure assignment in the computation of friends of output-nulling subspaces

    200868_200868.pdf (103.4Kb)
    Access Status
    Open access
    Authors
    Ntogramatzidis, Lorenzo
    Date
    2014
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Ntogramatzidis, L. 2014. Repeated eigenstructure assignment in the computation of friends of output-nulling subspaces, in van der Schaft, A. and Trentelman, H. and Scherpen, J. and de Persis, C. (ed), Proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems (MTNS), Jul 7-11 2014, pp. 1517-1522. Groningen, The Netherlands: University of Groningen.
    Source Title
    Proceedings of 21st International Symposium on Mathematical Theory of Networks and Systems
    Source Conference
    21st International Symposium on Mathematical Theory of Networks and Systems (MTNS 2014)
    ISBN
    9789036763219
    School
    Department of Mathematics and Statistics
    Remarks

    Copyright © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    URI
    http://hdl.handle.net/20.500.11937/30493
    Collection
    • Curtin Research Publications
    Abstract

    This paper is concerned with the parameterisation of basis matrices and the simultaneous computation of friends of the output nulling subspaces V*, V*g and R* with the assignment of the corresponding inner and outer closed-loop free eigenstructure. Differently from the classical techniques presented in the literature so far on this topic, which are based on the standard pole assignment algorithms and are therefore applicable only in the non-defective case, the method presented in this paper can be applied in the case of closed-loop eigenvalues with arbitrary multiplicity.

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