Universal approximation using differentiators and application to feedback control
Systems and Control
2011-02-15 v1 Optimization and Control
Abstract
In this paper, we consider the problems of approximating uncertainties and feedback control for a class of nonlinear systems without full-known states, and two approximation methods are proposed: universal approximation using integral-chain differentiator or extended observer. Comparing to the approximations by fuzzy system and radial-based-function (RBF) neural networks, the presented two methods can not only approximate universally the uncertainties, but also estimate the unknown states. Moreover, the integral-chain differentiator can restrain noises thoroughly. The theoretical results are confirmed by computer simulations for feedback control.
Keywords
Cite
@article{arxiv.1102.2794,
title = {Universal approximation using differentiators and application to feedback control},
author = {Xinhua Wang},
journal= {arXiv preprint arXiv:1102.2794},
year = {2011}
}