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基于时变NARMA模型的非线性时变系统辨识 被引量:5

NONLINEAR TIME-VARYING SYSTEM IDENTIFICATION BASED ON TIME-VARYING NARMA MODEL
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摘要 在非线性自回归滑动平均模型NARMA(NonlinearAutoRegressiveMovingAverage)中引入时间变量,将其扩展为时变NARMA模型,用Taylor展开将模型中的非线性函数展开为关于输入输出的多项式,得到关于参数线性时变的多项式形式的时变NARMA模型,再用基序列拟合模型的时变参数得到关于参数线性时不变的模型,最后用递推最小二乘法估计模型参数。仿真算例证明,与小波网络方法相比,辨识精度高,计算量小。 Introducing time variable into the NARMA (Nonlinear Auto Regressive Moving Average) model make it expand to time-varying NARMA model. The nonlinear function of the model can be expanded to a polynomial of input and output using Taylor expansion, and the polynomial time-varying NARMA model that is linear to the parameters is obtaine& Using base sequences to fit the time-varying parameters of the model, the nonlinear time-varying system is transformed into a time-invariant linear one, the parameters of which can be estimated by re.cursive least square algorithm. The results of simulation examples show that the identification accuracy and the computational complexity of this method are better than those of wavelet neural network method.
出处 《工程力学》 EI CSCD 北大核心 2006年第12期25-29,共5页 Engineering Mechanics
基金 国家自然科学基金资助项目(10672045)
关键词 非线性时变系统 系统辨识 NARMA 基序列拟合 递推最小二乘法 nonlinear time-varying system system identification NARMA base sequence fitting recursive least square method
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  • 1邹经湘,于开平,杨炳渊.时变结构的参数识别方法[J].力学进展,2000,30(3):370-377. 被引量:34
  • 2Yingwei L,Sundararajan N,Saratchandran P.Identification of time-varying nonlinear systems using minimal radial basis function neural networks[J].IEE Proceedings of Control Theory Applications,1997,144(2):202~208.
  • 3Apostolikas G,Tzafestas S.On-line RBFNN based identification of rapidly time-varying nonlinear systems with optimal structure-adaptation[J].Mathematics and Computers in Simulation,2003,63(1):1~13.
  • 4顾成奎,王正欧.基于前向神经网络的非线性时变系统辨识[J].管理科学学报,2001,4(3):36-39. 被引量:7
  • 5刘建春,王正欧.一种非线性时变系统小波网络辨识算法[J].系统工程学报,2002,17(5):401-406. 被引量:4
  • 6Nordsjo A E,Zetterberg L H.A reeursive prediction error algorithm for identification of certain time-varying nonlinear systems[J].IEEE International Conference on Acoustics,Speech,and Signal Processing,1999,3:1305~1308.
  • 7Boland M D,Zoubir A M.Identification of time-varying nonlinear systems with application to knock detection in combustion engines[J].IEEE Region 10 Annual Conference Speech and Image Technologies for Computing and Telecommunications,1997,2:799~802.
  • 8Green M,Zoubir A M.A search for parsimonious basis sequence approximation of time-varying nonlinear systems[J].IEEE international Symposium on Circuits and Systems,2000,1:148~151.
  • 9Nordsjo A E,Zetterberg L H.Identification of certain time-varying nonlinear wiener and hammerstein systems[J].IEEE Transactions on Signal Processing,2001,49(3):577~592.
  • 10Liu G P,Kadirkamanathan V,Billings S A.On-line identification of nonlinear systems using Volerra poly-nomial basis function neral networks[J].Neural Networks,1998,11(9):1645~1657.

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