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• W2005605304 abstract "This paper presents a decomposition based least squares estimation algorithm for a feedback nonlinear system with an output error model for the open-loop part by using the auxiliary model identification idea and the hierarchical identification principle and by decomposing a system into two subsystems. Compared with the auxiliary model based recursive least squares algorithm, the proposed algorithm has a smaller computational burden. The simulation results indicate that the proposed algorithm can estimate the parameters of feedback nonlinear systems effectively." @default.
• W2005605304 created "2016-06-24" @default.
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• W2005605304 date "2013-12-01" @default.
• W2005605304 modified "2023-10-13" @default.
• W2005605304 title "Auxiliary model based least squares parameter estimation algorithm for feedback nonlinear systems using the hierarchical identification principle" @default.
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• W2005605304 doi "https://doi.org/10.1016/j.jfranklin.2013.07.013" @default.
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