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Model variables identification of a gas turbine using a subspace approach based on input/output data measurements
HakimBagua,AhmedHafaifa,AbdelhamidIratni,MouloudGuemana
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(Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa, 17000 Djelfa, Algeria;Faculty of Science and Technology, University of Bordj Bou Arreridj, 34000 Bordj Bou Arreridj, Algeria;Gas Turbine Joint Research Team, University of Djelfa, 17000 Djelfa, Algeria)
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DOI:https://doi.org/10.1007/s11768-020-00005-z
基金项目:This paper is the result of the work of estimation and identification of gas turbine variables in real time, and was supported and carried out by the Gas Turbine Joint Research Team with the Applied Automation and Industrial Diagnostics Laboratory, University of Djelfa, Algeria. The authors express their sincere thanks to the General Directorate of Scientific Research and Technological Development (DGRSDT), Algeria.
Model variables identification of a gas turbine using a subspace approach based on input/output data measurements
Hakim Bagua,Ahmed Hafaifa,Abdelhamid Iratni,Mouloud Guemana
(Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa, 17000 Djelfa, Algeria;Faculty of Science and Technology, University of Bordj Bou Arreridj, 34000 Bordj Bou Arreridj, Algeria;Gas Turbine Joint Research Team, University of Djelfa, 17000 Djelfa, Algeria)
Abstract:
This paper deals with a state model identification of a gas turbine used for gas transport, using a subspace approach of the state space model. This method provides a reliable and robust state representation of the model, taking advantage of its benefits in the control, monitoring, and supervision of this machine. The model for each variable is set so that the state matrices associated with the gas turbine model are determined from their real input/output data. The comparison of the obtained 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 residual modeling error, and expresses a very high level of confidence in the identified turbine system dynamics. Hence, the controllability and observability tests of turbine operation for different input/output variables allowed to validate the real-time operating stability of the turbine.
Key words:  System identification · Subspace identification · State space model · Gas turbine · N4SID algorithm