A dynamic forgetting factor-based recursive estimation framework for radial basis function-based Hammerstein battery models

doi:10.1016/j.engappai.2025.113495

A dynamic forgetting factor-based recursive estimation framework for radial basis function-based Hammerstein battery models

2025-12-08

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Huafeng Xia

DOI：10.1016/j.engappai.2025.113495

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• The improved gradient-based online identification methods are proposed. • The presented RBF-Hammerstein model is parameterized by the key term separation technique. • The dynamic forgetting factor and the maximum likelihood principle are introduced.

A dynamic forgetting factor-based recursive estimation framework for radial basis function-based Hammerstein battery models

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