Prediction of Jet Engine Parameters for Control Design Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Martinez-Arellano:2014:UKSim,
  author =       "Giovanna {Martinez Arellano} and Richard Cant and 
                 Lars Nolle",
  booktitle =    "16th AMSS International Conference on Computer
                 Modelling and Simulation (UKSim 2014)",
  title =        "Prediction of Jet Engine Parameters for Control Design
                 Using Genetic Programming",
  year =         "2014",
  month =        mar,
  pages =        "45--50",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/UKSim.2014.64",
  size =         "6 pages",
  abstract =     "The simulation of a jet engine behaviour is widely
                 used in many different aspects of the engine
                 development and maintenance. Achieving high quality jet
                 engine control systems requires the iterative use of
                 these simulations to virtually test the performance of
                 the engine avoiding any possible damage on the real
                 engine. Jet engine simulations involve the use of
                 mathematical models which are complex and may not
                 always be available. This paper introduces an approach
                 based on Genetic Programming (GP) to model different
                 parameters of a small engine for control design such as
                 the Exhaust Gas Temperature (EGT). The GP approach has
                 no knowledge of the characteristics of the engine.
                 Instead, the model is found by the evolution of models
                 based on past measurements of parameters such as the
                 pump voltage. Once the model is obtained, it is used to
                 predict the behaviour of the jet engine one step ahead.
                 The proposed approach is successfully applied for the
                 simulation of a Behotec j66 jet engine and the results
                 are presented.",
  notes =        "Also known as \cite{7046037}",
}

Genetic Programming entries for Giovanna Martinez-Arellano Richard Cant Lars Nolle

Citations