Model variables identification of a gas turbine using a subspace approach based on input/output data measurements

This paper deals with a state model identification of a gas turbine used for gas transport, using a subspace approach of thestate space model. This method provides a reliable and robust state representation of the model, taking advantage of itsbenefits in the control, monitoring, and supervision of this machine. The model for each variable is set so that the statematrices associated with the gas turbine model are determined from their real input/output data. The comparison of theobtained identification results with those of the actual turbine operation serves to validate the proposed model in this work.This numerical algorithm of the subspace identification method is full of information and more accurate in terms of residualmodeling error, and expresses a very high level of confidence in the identified turbine system dynamics. Hence, the controllabilityand observability tests of turbine operation for different input/output variables allowed to validate the real-timeoperating stability of the turbine.