This brief reports the experience with the identification of a nonlinear autoregressive with exogenous inputs (NARX) model for the PGT10B1 power plant gas turbine manufactured by General Electric-Nuovo Pignone. Two operating conditions of the turbine are considered: isolated mode and nonisolated mode. The NARX model parameters are estimated iteratively with a Gram-Schmidt procedure, exploiting both forward and stepwise regression. Many indexes have been evaluated and compared in order to perform subset selection in the functional basis set and determine the structure of the nonlinear model. Various input signals (from narrow to broadband) for identification and validation have been considered.
NARX models of an industrial power plant gas turbine / M. Basso; L. Giarre; S. Groppi; G. Zappa. - In: IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY. - ISSN 1063-6536. - STAMPA. - 13:(2005), pp. 599-604. [10.1109/TCST.2004.843129]
NARX models of an industrial power plant gas turbine
BASSO, MICHELE;
2005
Abstract
This brief reports the experience with the identification of a nonlinear autoregressive with exogenous inputs (NARX) model for the PGT10B1 power plant gas turbine manufactured by General Electric-Nuovo Pignone. Two operating conditions of the turbine are considered: isolated mode and nonisolated mode. The NARX model parameters are estimated iteratively with a Gram-Schmidt procedure, exploiting both forward and stepwise regression. Many indexes have been evaluated and compared in order to perform subset selection in the functional basis set and determine the structure of the nonlinear model. Various input signals (from narrow to broadband) for identification and validation have been considered.File | Dimensione | Formato | |
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