Abstract
The paper proposes a data projection method for sensor faults detection and isolation in MIMO Hammerstein systems. The method uses the framework of subspace methods and does not need the system parameters or the nonlinear static input function knowledge. Only system input and output data are used for the faults detection and isolation. The method uses a polynomial approximation for the nonlinear static input function and matrix projection for a fault indicator signal generation. An academic example is provided to illustrate the applicability of the method.
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Pekpe, K.M. (2020). Data Projection Method for Sensor Faults Detection and Isolation in Hammerstein Systems. In: Adjallah, K., Birregah, B., Abanda, H. (eds) Data-Driven Modeling for Sustainable Engineering. ICEASSM 2017. Lecture Notes in Networks and Systems, vol 72. Springer, Cham. https://doi.org/10.1007/978-3-030-13697-0_1
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DOI: https://doi.org/10.1007/978-3-030-13697-0_1
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Online ISBN: 978-3-030-13697-0
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