Stochastic Gas Turbine Engine Models

  • Gennady G. Kulikov
  • Haydn A. Thompson
Part of the Advances in Industrial Control book series (AIC)


Previous chapters gave an overview of conventional methods for modelling of gas turbines for control purposes. This chapter provides basics of stochastic modelling using controllable Markov chain techniques. Accounting for stochastic properties is essential for engine modelling at system test facilities, where the real-life environment is simulated. In addition, the Markov modelling technique is a promising tool for condition monitoring and optimal control of aero engines. This chapter also introduces a novel fuzzy Markov modelling technique to further improve the modelling performance.


Markov Chain Transition Probability Matrix Control System Design Engine Model Random Disturbance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London 2004

Authors and Affiliations

  • Gennady G. Kulikov
    • 1
  • Haydn A. Thompson
    • 2
  1. 1.Department of Automated Control SystemsUfa State Aviation Technical UniversityRussia
  2. 2.Department of Automatic Control and Systems EngineeringThe University of SheffieldSheffieldUK

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