Title :
Recursive identification for Wiener model with discontinuous piece-wise linear function
Author_Institution :
Inst. of Syst. Sci., Acad. of Math. & Syst. Sci., Beijing, China
fDate :
3/1/2006 12:00:00 AM
Abstract :
This paper deals with identification of Wiener systems with nonlinearity being a discontinuous piece-wise linear function. Recursive estimation algorithms are proposed to estimate six unknown parameters contained in the nonlinearity and all unknown coefficients of the linear subsystem by using the iid Gaussian inputs. The estimates are proved to converge to the corresponding true values with probability one. A numerical example is given to justify the obtained theoretical results.
Keywords :
Gaussian processes; control nonlinearities; linear systems; piecewise linear techniques; recursive estimation; Gaussian inputs; Wiener model; discontinuous piecewise linear function; linear subsystem; recursive estimation algorithms; recursive identification; Biological system modeling; Computational biology; Convergence; Helium; Kernel; Nonlinear dynamical systems; Parameter estimation; Piecewise linear techniques; Recursive estimation; Systems biology; Identification; Wiener system; kernel function; strong consistency;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2005.864183