Title :
Strong consistency of recursive identification for Hammerstein systems with discontinuous piecewise-linear memoryless block
Author_Institution :
Key Lab. of Syst. & Control, Chinese Acad. of Sci., Beijing, China
Abstract :
This note deals with identification of Hammerstein systems with discontinuous piecewise-linear memoryless block followed by a linear subsystem. Recursive algorithms are proposed for estimating coefficients of the linear subsystem and six unknown parameters contained in the nonlinear static block. By taking a sequence of iid random variables with uniform distribution to serve as the system input, strong consistency is proved for all estimates given in the note. The theoretical results are verified by computer simulation.
Keywords :
linear systems; memoryless systems; nonlinear control systems; piecewise linear techniques; recursive estimation; sampled data systems; Hammerstein system; discontinuous piecewise linear memoryless block; linear subsystem; nonlinear static block; recursive identification; Additive noise; Computer simulation; Control systems; Least squares approximation; Nonlinear dynamical systems; Parameter estimation; Piecewise linear techniques; Polynomials; Random variables; Recursive estimation; Hammerstein system; least squares; parametric approach; recursive estimation; strong consistency;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2005.856658