基于时变narma模型的非线性时变系统辨识-oalib.pdfVIP

23 12 Vol.23 No.12 2006 12 Dec. 2006 ENGINEERING MECHANICS 25 1000-4750(2006)12-0025-05 NARMA * ( 150001) NARMA (Nonlinear Auto Regressive Moving Average) NARMA Taylor NARMA NARMA O32 A NONLINEAR TIME-VARYING SYSTEM IDENTIFICATION BASED ON TIME-VARYING NARMA MODEL * PANG Shi-wei , YU Kai-ping , ZOU Jing-xiang (Department of Astronautics and Mechanics, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China) Abstract: 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 obtained. 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 recursive 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. Key words: nonlinear time-varying system; system identification; NARMA; base sequence fitting; recursive least square method - MRBF (Minimal Radial Basis Function)[2] [1] Kalman