Title :
Convergence of the iterative Hammerstein system identification algorithm
Author :
Bai, Er-Wei ; Li, Duan
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA
Abstract :
The convergence of the iterative identification algorithm for the Hammerstein system has been an open problem for a long time. In this paper, a detailed study is carried out and various convergence properties of the iterative algorithm are derived. It is shown that the iterative algorithm with normalization is convergent in general. Moreover, it is shown that convergence takes place in one step (two least squares iterations) for finite-impulse response Hammerstein models with i.i.d. inputs.
Keywords :
cascade systems; convergence of numerical methods; identification; iterative methods; least mean squares methods; nonlinear control systems; Hammerstein system; finite impulse response; iterative identification algorithm convergence; least square iterations; nonlinear systems; Convergence; Frequency domain analysis; Helium; Iterative algorithms; Least squares methods; Nonlinear dynamical systems; Nonlinear systems; Parameter estimation; Stochastic processes; System identification; 65; Hammerstein systems; nonlinear systems; parameter estimation; system identification;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2004.837592
