Adaptive Observers and Parameter Estimation for a Class of Systems Nonlinear in the Parameters
Abstract
We consider the problem of asymptotic reconstruction of the state and parameter values in systems of ordinary differential equations. A solution to this problem is proposed for a class of systems of which the unknowns are allowed to be nonlinearly parameterized functions of state and time. Reconstruction of state and parameter values is based on the concepts of weakly attracting sets and non-uniform convergence and is subjected to persistency of excitation conditions. In absence of nonlinear parametrization the resulting observers reduce to standard estimation schemes. In this respect, the proposed method constitutes a generalization of the conventional canonical adaptive observer design.
Cite
@article{arxiv.0903.2361,
title = {Adaptive Observers and Parameter Estimation for a Class of Systems Nonlinear in the Parameters},
author = {Ivan Y. Tyukin and Erik Steur and Henk Nijmeijer and Cees van Leeuwen},
journal= {arXiv preprint arXiv:0903.2361},
year = {2015}
}
Comments
Preliminary version is presented at the 17-th IFAC World Congress, 6-11 Seoul, 2008