Title :
NARX models of an industrial power plant gas turbine
Author :
Basso, M. ; Giarre, L. ; Groppi, S. ; Zappa, G.
Author_Institution :
Dipt. di Sistemi e Informatica, Univ. di Firenze, Italy
fDate :
7/1/2005 12:00:00 AM
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.
Keywords :
autoregressive processes; gas turbine power stations; gas turbines; nonlinear control systems; parameter estimation; Gram-Schmidt procedure; industrial power plant gas turbine; nonlinear autoregressive with exogenous inputs model; nonlinear system; parameter estimation; stepwise regression; Drives; Gas industry; Parameter estimation; Power generation; Power grids; Power system interconnection; Power system modeling; Power system reliability; Power system transients; Turbines; Gas turbines; identification; modeling; nonlinear systems; power systems; turbines;
Journal_Title :
Control Systems Technology, IEEE Transactions on
DOI :
10.1109/TCST.2004.843129