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Application of an optimal tuner selection approach for on-board self-tuning engine models / Donald L. Simon in Transactions of the ASME . Journal of engineering for gas turbines and power, Vol. 134 N° 4 (Avril 2012) 

Public ISBD [article]  in Transactions of the ASME . Journal of engineering for gas turbines and power > Vol. 134 N° 4 (Avril 2012) . - 11 p. Titre : Application of an optimal tuner selection approach for on-board self-tuning engine models Type de document : texte imprimé Auteurs : Donald L. Simon, Auteur ; Jeffrey B. Armstrong, Auteur ; Sanjay Garg, Auteur Année de publication : 2012 Article en page(s) : 11 p. Note générale : Génie mécanique Langues : Anglais (eng) Mots-clés : Aerospace  engines  Aircraft  control  Closed  loop  systems  Dynamic  response  Kalman  filters  Mean  square  error  methods  Open  loop  systems  Optimisation  Self-adjusting  systems  State  estimation Index. décimale : 620.1 Essais des matériaux. Défauts des matériaux. Protection des matériaux Résumé : An enhanced design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented in this paper. It specifically addresses the under-determined estimation problem, in which there are more unknown parameters than available sensor measurements. This work builds upon an existing technique for systematically selecting a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. While the existing technique was optimized for open-loop engine operation at a fixed design point, in this paper an alternative formulation is presented that enables the technique to be optimized for an engine operating under closed-loop control throughout the flight envelope. The theoretical Kalman filter mean squared estimation error at a steady-state closed-loop operating point is derived, and the tuner selection approach applied to minimize this error is discussed. A technique for constructing a globally optimal tuning parameter vector, which enables full-envelope application of the technology, is also presented, along with design steps for adjusting the dynamic response of the Kalman filter state estimates. Results from the application of the technique to linear and nonlinear aircraft engine simulations are presented and compared to the conventional approach of tuner selection. The new methodology is shown to yield a significant improvement in on-line Kalman filter estimation accuracy. DEWEY : 620.1 ISSN : 0742-4795 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JETPEZ000134000004 [...] [article] Application of an optimal tuner selection approach for on-board self-tuning engine models [texte imprimé] / Donald L. Simon, Auteur ; Jeffrey B. Armstrong, Auteur ; Sanjay Garg, Auteur . - 2012 . - 11 p. Génie mécanique Langues : Anglais (eng) in Transactions of the ASME . Journal of engineering for gas turbines and power > Vol. 134 N° 4 (Avril 2012) . - 11 p. Mots-clés : Aerospace  engines  Aircraft  control  Closed  loop  systems  Dynamic  response  Kalman  filters  Mean  square  error  methods  Open  loop  systems  Optimisation  Self-adjusting  systems  State  estimation Index. décimale : 620.1 Essais des matériaux. Défauts des matériaux. Protection des matériaux Résumé : An enhanced design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented in this paper. It specifically addresses the under-determined estimation problem, in which there are more unknown parameters than available sensor measurements. This work builds upon an existing technique for systematically selecting a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. While the existing technique was optimized for open-loop engine operation at a fixed design point, in this paper an alternative formulation is presented that enables the technique to be optimized for an engine operating under closed-loop control throughout the flight envelope. The theoretical Kalman filter mean squared estimation error at a steady-state closed-loop operating point is derived, and the tuner selection approach applied to minimize this error is discussed. A technique for constructing a globally optimal tuning parameter vector, which enables full-envelope application of the technology, is also presented, along with design steps for adjusting the dynamic response of the Kalman filter state estimates. Results from the application of the technique to linear and nonlinear aircraft engine simulations are presented and compared to the conventional approach of tuner selection. The new methodology is shown to yield a significant improvement in on-line Kalman filter estimation accuracy. DEWEY : 620.1 ISSN : 0742-4795 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JETPEZ000134000004 [...]