一种求取发动机状态变量模型的改进拟合法
An improved method of identification for aero-engine's state variable model
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摘要: 采用的拟合辨识方法是直接对根据状态变量模型中各变量间的线性关系对系数矩阵进行拟合,并且实现对稳态过程和瞬态过程进行分步拟合,从而消除瞬态误差对稳态精度的影响.本方法有接近传统最小二乘法的精度,并且无需求解状态变量模型微分方程或使用迭代算法,只需要进行简单的矩阵运算即可得到各系数矩阵,因此计算效率远高于传统最小二乘法.同时,该方法也可与其他拟合方法结合使用从而进一步提高拟合精度.最后,应用该方法建立了某涡轴发动机的小偏差状态变量模型,通过与非线性模型仿真结果比较,验证了该方法的有效性,即使对象非线性较强,该方法也能得到精度较高的拟合效果.Abstract: The method for aeroengines' state variable model(SVM)identification was implemented by using the linear relation of the variable of the differential equations,and separating the steady process and transient process to eliminate the steady errors coupled by transient process. Without solving the differential equations or using any iterative methods, the coefficient of the SVM could be acquired simply using matrix operation, so it has a higher computational efficiency than former least square method. And this method might also be combined with other identification method to realize better effect. Finally, to illustrate the validity and accuracy of the proposed method, a small perturbation SVM of some turbo-shaft engine model had been established through it, and the simulation results from the engine's state space model and nonlinear model were compared,and we can draw a conclusion that the SVM got by this method meets the dynamic and static objectives well, though the plant has a severe nonlinearity.
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Key words:
- aero-engine /
- state variable model /
- identification method /
- steady process /
- transient process
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[1] Leibov R.Aircraft turbofan engine linear model with uncertain eigenvalues[J].IEEE Transaction on Automatic Control,2002,47(8):1367-1369. [2] Geyser L C.DYGABCD2A program for calculating linear A,B,C and D matrices from a nonlinear dynamic engine model.NASA NP21295,1978. [3] Daniele C J,Krosel S M.Generation of linear dynamic models from a digital nonlinear simulation.NASA NP21388,1979. [4] Sugiyama N.Derivation of ABCD system mat rices from nonlinear dynamic simulation of jet engines.AIAA 92-3319,1992. [5] 黄伟斌,黄金泉.航空发动机故障诊断的自适应模型[J].航空动力学报,2008,23(3):580-584. HUANG Weibin,HUANG Jinquan.On board self-tuning model for aero-engine fault diagnostics[J].Journal of Aerospace Power,2008,23(3):580-584.(in Chinese) [6] 冯正平,孙健国,黄金泉,等.一种建立航空发动机状态变量模型的新方法[J].航空动力学报,1998,13(4):435-438. FENG Zhengping,SUN Jianguo,HUANG Jinquan,et al.A new method for establishing a state space model of aeroengine[J].Journal of Aerospace Power,1998,13(4):435-438.(in Chinese) [7] 郑铁军,王曦,罗秀芹,等.建立航空发动机状态空间模型的修正方法[J].推进技术,2005,26(1):46-49. ZHENG Tiejun,WANG Xi,LUO Xiuqin,et al.Modified method of establishing the state space model of aeroengine[J].Journal of Propulsion Technology,2005,26(1):46-49.(in Chinese) [8] Merrill W C,Lehtinen B,Zeller J.The role of modern control theory in the design of controls for aircraft turbine engines[J].Journal of Guidance,Control,and Dynamics,1984,7(6):652-661. [9] 冯正平,孙健国.航空发动机小偏差状态变量模型的建立方法[J].推进技术,2001,22(1):54-57. FENG Zhengping,SUN Jianguo.Modeling of small perturbation state variable model for aeroengines[J].Journal of Propulsion Technology,2001,22(1):54-57.(in Chinese) [10] 周文祥,单晓明,耿志东,等.自寻优求解法建立涡轴发动机状态变量模型[J].航空动力学报,2008,23(12):2314-2320. ZHOU Wenxiang,SHAN Xiaoming,GENG Zhidong,et al.Establishment of state space model of turboshaft engine with self-optimized method[J].Journal of Aerospace Power,2008,23(12):2314-2320.(in Chinese) [11] 张海波,孙健国,孙丰诚.非线性反演控制律在航空发动机多变量控制中的应用[J].航空动力学报,2007,22(7):1190-1194. ZHANG Haibo,SUN Jianguo,SUN Fengcheng.Applications of nonlinear backstepping control strategy in multivariable control of aeroengine[J].Journal of Aerospace Power,2007,22(7):1190-1194.(in Chinese) [12] 李秋红,孙健国.航空发动机大偏差状态变量模型建立方法[J].南京航空航天大学学报,2010,42(2):175-178. LI Qiuhong,SUN Jianguo.Aero-engine large-deviation state variable modeling[J].Journal of Nanjing University of Aeronautics and Astronautics,2010,42(2):175-178.(in Chinese)
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