Multiobjective genetic programming for gas turbine engine model identification

A genetic programming-NARMAX approach has been successful applied to the identification of nonlinear systems. This evolutionary identification method has been extended to a multiobjective form with the aim of simultaneously optimising different measures of the system model under investigation. So fa...

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Bibliographic Details
Published inIEE conference publication pp. 1385 - 1390
Main Authors Rodriguez-Vazquez, K, Fleming, P.J
Format Conference Proceeding
LanguageEnglish
Published London IEE 1998
Subjects
Applied sciences
Computer science; control theory; systems
Control of heat systems
Control theory. Systems
Exact sciences and technology
Modelling and identification
Optimisation techniques
Other topics in statistics
Simulation, modelling and identification
nonlinear systems
dynamics
genetic programming
identification
NARMAX model
gas turbine engine
autoregressive moving average processes
gas turbines
genetic algorithms
shaft speed
multiobjective optimisation
ARMAX model
Genetic algorithm
Multiobjective programming
System identification
Gas turbine
Non linear system
Optimization
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Summary:A genetic programming-NARMAX approach has been successful applied to the identification of nonlinear systems. This evolutionary identification method has been extended to a multiobjective form with the aim of simultaneously optimising different measures of the system model under investigation. So far, this novel approach has only been tested on simulated data. Here, we demonstrate a practical application of this technique to obtain a model of the relationship between the fuel feed and the shaft speed dynamics of a gas turbine engine.
ISBN:085296708X
9780852967089
ISSN:0537-9989
DOI:10.1049/cp:19980432