Abstract
The aim of this paper is to present a novel approach to closed-loop discrete-time system frequency response and the corresponding parametric model identification using repeated discrete-time non-Gaussian excitation and quantized plant output observartions. The specially designed identification experiment based on data averaging is proposed to reduce the quantization effect and enhance signal-to-noise ratio. The integrated bispectra-based identification method is proposed to handle with closed-loop system identification problems. A focus on model identification in the case of disturbance-free plant output and output signal level comparable with data acquisition system accuracy is given. Convergence of the identified model to true plant is discussed. The discussion is illustrated by an example showing properties of the presented approach.
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Główka, T., Figwer, J. (2014). Closed-Loop System Identification Using Quantized Observations and Integrated Bispectra. In: Swiątek, J., Grzech, A., Swiątek, P., Tomczak, J. (eds) Advances in Systems Science. Advances in Intelligent Systems and Computing, vol 240. Springer, Cham. https://doi.org/10.1007/978-3-319-01857-7_74
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DOI: https://doi.org/10.1007/978-3-319-01857-7_74
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01856-0
Online ISBN: 978-3-319-01857-7
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