A Fitting Method for Establishing an Aeroengine’s State Variable Model Based on Process Identification

Abstract:

The bias derivative method for aeroengine’s State Variable Model(SVM) doesn’t have a satisfying accuracy. This method usually needs a linear modification to achieve a higher accuracy. In order to obtain a SVM with a good accuracy, this paper proposes a process identification based method. In this method, the coefficient matrices of the SVM are identified based on the input and output of the nonlinear model, according to the principle that the step responses of the SVM and the nonlinear model should be consistent. Then, the SVMs of small perturbation about steady operating points of an engine are established. Simulation results show that the SVMs established by the process identification based method have a good fidelity both in terms of steady and dynamic performance.

• Periodical: Applied Mechanics and Materials (Volumes 236-237)
• Pages: 1356-1361
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.236-237.1356
• Online since: November 2012
• Authors: Xiang Xing Kong, Xi Wang
• Keywords: Aeroengine, Process Identification, State Variable Model

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