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- W3132378160 abstract "This paper deals with the identification of the fractional order Hammerstein model by using proposed adaptive differential evolution with the Local search strategy (ADELS) algorithm with the steepest descent method and the overparameterization based auxiliary model recursive least squares (OAMRLS) algorithm. The parameters of the static nonlinear block and the dynamic linear block of the model are all unknown, including the fractional order. The initial value of the parameter is obtained by the proposed ADELS algorithm. The main innovation of ADELS is to adaptively generate the next generation based on the fitness function value within the population through scoring rules and introduce Chebyshev mapping into the newly generated population for local search. Based on the steepest descent method, the fractional order identification using initial values is derived. The remaining parameters are derived through the OAMRLS algorithm. With the initial value obtained by ADELS, the identification result of the algorithm is more accurate. The simulation results illustrate the significance of the proposed algorithm." @default.
- W3132378160 created "2021-03-01" @default.
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- W3132378160 date "2021-02-23" @default.
- W3132378160 modified "2023-10-16" @default.
- W3132378160 title "Recursive Identification for Fractional Order Hammerstein Model Based on ADELS" @default.
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- W3132378160 doi "https://doi.org/10.1155/2021/6629820" @default.
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