Model variables identification of a gas turbine using a subspace approach based on input/output data measurements
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RESEARCH ARTICLE
Model variables identification of a gas turbine using a subspace approach based on input/output data measurements Hakim Bagua1,2 · Ahmed Hafaifa1,2 · Abdelhamid Iratni3 · Mouloud Guemana2 Received: 31 May 2020 / Revised: 27 July 2020 / Accepted: 19 August 2020 © South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2020
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. Keywords System identification · Subspace identification · State space model · Gas turbine · N4SID algorithm
1 Introduction Gas turbines have experienced great expansion in many industrial applications around the world, particularly in the energy production sector or in the gas transport. These machines are increasing in performance and complexity. In fact, the activity of monitoring these rotating machines is very challenging and requires a large amount of information * Ahmed Hafaifa a.hafaifa@univ‑djelfa.dz Hakim Bagua H.Bagua@univ‑djelfa.dz Abdelhamid Iratni iratni@univ‑bba.dz Mouloud Guemana guemana.mouloud@univ‑medea.dz 1
Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa, 17000 Djelfa, Algeria
2
Gas Turbine Joint Research Team, University of Djelfa, 17000 Djelfa, Algeria
3
Faculty of Science and Technology, University of Bordj Bou Arreridj, 34000 Bordj Bou Arreridj, Algeria
and data, with regard to the functioning of these processes, to guarantee a proper level of real-time surveillance. For this, the dynamics of these machines, and their stability analysis, serve as a substantial database for models aiming the enhancement of the security and performance aspects of these systems. Several monitoring solutions and approaches have been proposed in several works to overcome these control problems of gas turbines and their use in real time [1–6]. Indeed, the system identification using the subspace strategy determines, from the inputs and outputs measurements, the observability and the sequence state
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