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• W3200124918 abstract "Fractional-order calculus has already proven to be effective in order to model diffusive phenomena, such as heat transfer or anomalous mass transfer. This has led to developments of fractional-order transfer function models and, as a consequence, system identification algorithms have been developed to identify the parameters for this type of structures. However, it may be necessary to perform real-time system identification in which the parameters evolve over time while more and more data is acquired. Extensions to recursive identification algorithms are presented for fractional-order transfer functions. Two methods are proposed for recursive estimation of the coefficients of continuous-time fractional order systems: the recursive least squares with state variable filters and the prediction-error method. These two methods are compared with different signal to noise ratio levels through Monte Carlo simulations." @default.
• W3200124918 created "2021-09-27" @default.
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• W3200124918 date "2021-01-01" @default.
• W3200124918 modified "2023-09-25" @default.
• W3200124918 title "Recursive system identification for coefficient estimation of continuous-time fractional order systems" @default.
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• W3200124918 doi "https://doi.org/10.1016/j.ifacol.2021.08.344" @default.
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