Title :
Identification of linearly overparametrized nonlinear systems
Author :
Bastin, G. ; Bitmead, R.R. ; Campion, G. ; Gevers, M.
Author_Institution :
Lab. d´´Autom., Catholic Univ. of Louvain, Belgium
Abstract :
Often, a dynamical model is nonlinear in the unknown parameters, but it can be transformed into an overparameterized linear regression model, where the components of the overparameterization vector are nonlinear functions of the smaller number of unknown parameters. An algorithm that directly identifies the unknown parameters is presented, and the convergence domain is characterized
Keywords :
nonlinear systems; parameter estimation; statistics; convergence domain; dynamical model; linearly overparametrized nonlinear systems; overparameterized linear regression model; parameter estimation; parameter identification; statistics; Circuits; Convergence; Linear regression; Linear systems; Nonlinear systems; Parameter estimation; Polynomials; Signal mapping; Systems engineering and theory; Vectors;
Conference_Titel :
Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
Conference_Location :
Tampa, FL
DOI :
10.1109/CDC.1989.70191
