Identification of nonlinear errors-in-variables models

The paper is about a generalization of a classical eigenvalue-decomposition method originally developed for errors–in-variables linear system identification to handle an important class of nonlinear problems. A number of examples are presented to call the attention to the most critical part of the procedure turning the identification problem to a generalized eigenvalue-eigenvector calculation problem with symmetrical matrices. The elaborated method generates consistent parameter estimation. Simulation results demonstrate the effectiveness of the proposed algorithm. Copyright © 2002 IFAC