Application of Markov chains to identification of gas turbine engine dynamic models

Authors:
T. V. Breikin;V. Y. Arkov;G. G. Kulikov
Affiliations:
Control Systems Centre, Department of Electrical Engineering and Electronics, University of Manchester, Institute of Science and Technology, Manchester, UK;Department of Automated Control Systems, Ufa State Aviation Technical University, Ufa, Russia;Department of Automated Control Systems, Ufa State Aviation Technical University, Ufa, Russia
Venue:
International Journal of Systems Science
Year:
2006

Citing 3
Cited 1

System identification

System identification
Digital Control Systems

Digital Control Systems
Brief On-line performance optimisation of aero engine control system

Automatica (Journal of IFAC)

Diagnosis of fuel pump measurement bias in gas turbine engines

International Journal of Systems Science

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper addresses the practical problems of dynamic modelling of aero gas turbine engines for condition-monitoring purposes. The Markov chain technique is implemented to perform identification of the engine dynamic models using the engine normal flight data. This includes identifiability analysis and model estimation. When identifying the model, experimental data should be sufficiently informative for identification. A possible technique for identifiability analysis is proposed on the basis of non-parametric models in the form of controllable Markov chains. At the stage of the model estimation, Markov chains are introduced to provide more functionality and versatility for dynamic modelling of gas turbines.