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Model parameters estimation of aero-engine based on hybrid optimization algorithm

LIQiu-hong

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文章导航 > 航空动力学报  > 2011 >  26(7): 1665-1671
LIQiu-hong. Model parameters estimation of aero-engine based on hybrid optimization algorithm[J]. 航空动力学报, 2011, 26(7): 1665-1671.
引用本文: LIQiu-hong. Model parameters estimation of aero-engine based on hybrid optimization algorithm[J]. 航空动力学报, 2011, 26(7): 1665-1671.
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LI Qiu-hong. Model parameters estimation of aero-engine based on hybrid optimization algorithm[J]. Journal of Aerospace Power, 2011, 26(7): 1665-1671.
Citation: LI Qiu-hong. Model parameters estimation of aero-engine based on hybrid optimization algorithm[J]. Journal of Aerospace Power, 2011, 26(7): 1665-1671.
shu

Model parameters estimation of aero-engine based on hybrid optimization algorithm

Model parameters estimation of aero-engine based on hybrid optimization algorithm

    摘要
  • 摘要: A hybrid optimization algorithm for the time-domain identification of multivariable,state space model for aero-engine was presented in this paper.The optimization procedure runs particle swarm optimization (PSO) and least squares optimization (LSO) "in series".PSO starts from an initial population and searches for the optimum solution by updating generations.However,it can sometimes run into a suboptimal solution.Then LSO can start from the suboptimal solution of PSO,and get an optimum solution by conjugate gradient algorithm.The algorithm is suitable for the high-order multivariable system which has many parameters to be estimated in wide ranges.Hybrid optimization algorithm is applied to estimate the parameters of a 4-input 4-output state variable model (SVM) for aero-engine.The simulation results demonstrate the effectiveness of the proposed algorithm.

     

    Abstract: A hybrid optimization algorithm for the time-domain identification of multivariable,state space model for aero-engine was presented in this paper.The optimization procedure runs particle swarm optimization (PSO) and least squares optimization (LSO) "in series".PSO starts from an initial population and searches for the optimum solution by updating generations.However,it can sometimes run into a suboptimal solution.Then LSO can start from the suboptimal solution of PSO,and get an optimum solution by conjugate gradient algorithm.The algorithm is suitable for the high-order multivariable system which has many parameters to be estimated in wide ranges.Hybrid optimization algorithm is applied to estimate the parameters of a 4-input 4-output state variable model (SVM) for aero-engine.The simulation results demonstrate the effectiveness of the proposed algorithm.

     

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    • 参考文献(13)
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    [7] Ling S H,Iu H,Leung F H F,et al.Improved hybrid particle swarm optimized wavelet neural network for modeling the development of fluid dispensing for electronic packaging[J].Industrial Electronics,IEEE Transactions on,2008,55(9):3447-3459.
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    [12] YUAN Chunfei,YAO Hua,YANG Gang.On-board real-time adaptive model of aero-engine[J].Chinese Journal of Aeronautics,2006,27(4):561-564.(in Chinese)
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出版历程
  • 收稿日期:  2010-06-29
  • 修回日期:  2011-03-02
  • 刊出日期:  2011-07-28

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