Artículos de revistas
An IV-QR algorithm for neuro-fuzzy multivariable online identification
Registro en:
Ieee Transactions On Fuzzy Systems. Ieee-inst Electrical Electronics Engineers Inc, v. 15, n. 2, n. 200, n. 210, 2007.
1063-6706
WOS:000245684800006
10.1109/TFUZZ.2006.879997
Autor
Serra, G
Bottura, C
Institución
Resumen
In this paper, a new algorithm for neuro-fuzzy identification of multivariable discrete-time nonlinear dynamic systems, more specifically applied to consequent parameters estimation of the neuro-fuzzy inference system, is proposed based on a decomposed form as a set of coupled multiple input and single output (MISO) Takagi-Sugeno (TS) neuro-fuzzy networks. An on-line scheme is formulated for modeling a nonlinear autoregressive with exogenous input (NARX) recurrent neuro-fuzzy structure from input-output samples of a multivariable nonlinear dynamic system in a noisy environment. The adaptive weighted instrumental variable (WIV) algorithm by QR factorization based on the numerically robust orthogonal Householder transformation is developed to modify the consequent parameters of the TS multivariable neuro-fuzzy network. 15 2 200 210