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- W4320803216 abstract "The multivariable Hammerstein system has been widely used in various complex industrial systems. Therefore, it is very important to identify the parameters of this type of systems. Due to the complexity and diversity of the nonlinear part in the multivariable Hammerstein system, the difficulty of system identification increases. The improved chaotic gravitational search algorithm (ICGSA) is used to estimate the parameters of the static nonlinear part, the linear part and the colored noise part in the multivariable Hammerstein systems. The simulation results show that the ICGSA can effectively identify the multivariable Hammerstein systems. In addition, the ICGSA is proved to be superior to the chaotic gravitational search algorithm (CGSA) and the forgetting factor stochastic gradient algorithm (FFSG) in identification accuracy by comparing with CGSA and FFSG." @default.
- W4320803216 created "2023-02-15" @default.
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- W4320803216 date "2022-08-15" @default.
- W4320803216 modified "2023-09-23" @default.
- W4320803216 title "Improved gravitational search and identification of multivariable Hammerstein systems" @default.
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- W4320803216 doi "https://doi.org/10.1109/ccdc55256.2022.10034280" @default.
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