Title :
Finite model order accuracy analysis in Wiener system identification
Author_Institution :
Sch. of Mech. & Electron. Eng., Jingdezhen Ceramic Inst., Jingdezhen, China
Abstract :
To two class unknown parameter vectors from Wiener system which were combined in nonlinear function, we can use prediction error method to identify these two class unknown parameter vectors and furthermore determine the asymptotic covariance matrix expressions of the system object model and noise model between Wiener system. In generalized case we construct a optimization problem which include the input power density based on this paper´s asymptotic covariance matrix expressions. By solve this optimization problem with some constrained condition, the optimal input signal spectrum about Wiener system is obtained. Finally, the efficiency and possibility of the proposed strategy can be confirmed by the simulation example results.
Keywords :
covariance matrices; nonlinear functions; optimisation; parameter estimation; prediction theory; vectors; Wiener system identification; asymptotic covariance matrix expressions; constrained condition; finite model order accuracy analysis; input power density; noise model; nonlinear function; optimal input signal spectrum; optimization problem; prediction error method; system object model; two class unknown parameter vectors; Accuracy; Analytical models; Covariance matrix; Electronic mail; Predictive models; System identification; Vectors; Wiener system; asymptotic analysis; finite order; input signal design; prediction error method; system identification;
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
Print_ISBN :
978-1-4673-2581-3