Model parameters estimation of aero-engine based on hybrid optimization algorithm |
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| Authors: | LI Qiu-hong |
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| Affiliation: | （College of Energy and Power EngineeringNanjing University of Aeronautics and Astronautics, Nanjing 210016, China |
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| 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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| Keywords: | aero-engine state variable model (SVM) particle swarm optimization (PSO) least squares optimization (LSO) hybrid optimization algorithm |
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