System Identification Strategies Applied to Aircraft Gas Turbine Engines

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Arkov:2000:ARC,

• author = "V. Arkov and C. Evans and P. J. Fleming and D. C. Hill and J. P. Norton and I. Pratt and D. Rees and K. Rodriguez-Vazquez",
• title = "System Identification Strategies Applied to Aircraft Gas Turbine Engines",
• journal = "Annual Reviews in Control",
• volume = "24",
• pages = "67--81",
• year = "2000",
• number = "1",
• keywords = "genetic algorithms, genetic programming, gas turbines, system identification, frequency domain, multisine signals least-squares estimation, time-varying systems, structure selection",
• ISSN = "1367-5788",
• broken = "http://www.sciencedirect.com/science/article/B6V0H-482MDPD-8/2/dd470648e2228c84efe7e14ca3841b7e",
• DOI = "doi:10.1016/S1367-5788(00)90015-4",
• size = "15 pages",
• abstract = "A variety of system identification techniques are applied to the derivation of models of aircraft gas turbine dynamics. The motivation behind the study is to improve the efficiency and cost-effectiveness of system identification techniques currently used in the industry. Four system identification approaches are outlined in this paper. They are based upon: identification using ambient noise only data, multisine testing and frequency-domain identification, time-varying models estimated using extended least squares with optimal smoothing, and multiobjective genetic programming to select model structure.",
• notes = "Also known as \cite{Arkov200067}",

}

Genetic Programming entries for V Arkov C Evans Peter J Fleming D C Hill J P Norton I Pratt D Rees Katya Rodriguez-Vazquez

Citations