Studies in Informatics and Control – ICI Bucharest
Merouane ALAOUI1, Obaid S. ALSHAMMARI2, Abdelhamid IRATNI1,4, Ahmed HAFAIFA1, 3*, Houssem JERBI2
1 Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology,
University of Djelfa 17000 DZ, Algeria
m.alaoui@univ-djelfa.dz, a.hafaifa@univ-djelfa.dz
2 Electrical Engineering department, University of Ha’il, The Kingdom of Saudi Arabia
os.alshammari@uoh.edu.sa, h.jerbi@uoh.edu.sa
3 Department of Electrical and Electronics Engineering, Nisantasi University, 34398 Sarıyer, Istanbul, Turkey
ahmed.hafaifa@nisantasi.edu.tr (*Corresponding author)
4 Faculty of Science and Technology, University of Bordj Bou Arreridj, 34030 DZ, Algeria
iratni@univ-bba.dz
Abstract: The outstanding performance of modern gas turbine power plants requires an efficient and robust control strategy in order to recover the losses caused by the undesirable effects and the instabilities related to their operation. Also, these losses can be the cause of their unstable dynamic behaviour during full-load and partial load operation in the unplanned shutdown state. Hence, choosing the right control strategy can improve the operation of this type of machine by increasing its efficiency by up to 60%. This paper proposes the implementation of an innovative control strategy based on a generalized predictive adaptive control algorithm for monitoring the rotation speed of a Solar Titan 130 gas turbine, with the purpose of considering the constraints related to the nonlinear behavior of a turbine during large variations in machine load. The aim is to automatically adjust the parameters of the regulator of the turbine’s control loop in real time, with a recursive estimation of these parameters. Using the experimental input/output measurements in order to study its behavior, by integrating the predictive control estimators, ensures the superior performance of the analyzed gas turbine in terms of energy, efficiency and robustness regarding the parametric uncertainties and the variation of the turbine load.
Keywords: Control adaptation algorithm, Generalized predictive adaptive control, Experimental measurements, Linear models, Control robustness and monitoring, Gas turbine, Turbine rotation speed.
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CITE THIS PAPER AS:
Merouane ALAOUI, Obaid S. ALSHAMMARI, Abdelhamid IRATNI, Ahmed HAFAIFA, Houssem JERBI, Gas Turbine Speed Monitoring Using a Generalized Predictive Adaptive Control Algorithm, Studies in Informatics and Control, ISSN 1220-1766, vol. 31(3), pp. 87-96, 2022. https://doi.org/10.24846/v31i3y202208