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    High-order sliding mode observer for fractional commensurate linear systems with unknown input

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    Type
    Article
    Authors
    Belkhatir, Zehor cc
    Laleg-Kirati, Taous-Meriem cc
    KAUST Department
    Computational Bioscience Research Center (CBRC)
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2017-05-20
    Online Publication Date
    2017-05-20
    Print Publication Date
    2017-08
    Permanent link to this record
    http://hdl.handle.net/10754/625005
    
    Metadata
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    Abstract
    In this paper, a high-order sliding mode observer (HOSMO) is proposed for the joint estimation of the pseudo-state and the unknown input of fractional commensurate linear systems with single unknown input and a single output. The convergence of the proposed observer is proved using a Lyapunov-based approach. In addition, an enhanced variant of the proposed fractional-HOSMO is introduced to avoid the peaking phenomenon and thus to improve the estimation results in the transient phase. Simulation results are provided to illustrate the performance of the proposed fractional observer in both noise-free and noisy cases. The effect of the observer’s gains on the estimated pseudo-state and unknown input is also discussed.
    Citation
    Belkhatir Z, Laleg-Kirati TM (2017) High-order sliding mode observer for fractional commensurate linear systems with unknown input. Automatica 82: 209–217. Available: http://dx.doi.org/10.1016/j.automatica.2017.04.035.
    Sponsors
    The authors would like to thank the anonymous referees and associate editor for their careful reading and useful suggestions that helped them to improve the quality of this paper. They would also like to thank Professor Mohamed Djemai, from university of Valenciennes et Hainaut-Cambrésis in France, for his valuable suggestions and comments.
    Publisher
    Elsevier BV
    Journal
    Automatica
    DOI
    10.1016/j.automatica.2017.04.035
    Additional Links
    http://www.sciencedirect.com/science/article/pii/S0005109817302297
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.automatica.2017.04.035
    Scopus Count
    Collections
    Articles; Electrical and Computer Engineering Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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