Nonfragile high‐gain observers for nonlinear systems with output uncertainty

Author:

Zhou Fan12,Shen Yanjun1ORCID,Xia Xiaohua3

Affiliation:

1. College of Electrical Engineering and New Energy China Three Gorges University Yichang Hubei China

2. State Grid Hubei Direct Current Operation Research Institute Yichang Hubei China

3. College of Electrical Electronic and Computer Engineering University of Pretoria Pretoria South Africa

Abstract

AbstractIn this paper, we present the definitions of nonfragile high‐gain observers and design method for lower‐triangular nonlinear systems with output uncertainty. Radial basis function neural networks (RBFNNs) are used to approximate the output uncertainty. By inserting an output filter and an input‐output filter, a new augmented adaptive observable canonical form is derived. Then, a corresponding observer with gain perturbations is designed to estimate the states and the coefficients of the RBFNNs, and a disturbance observer is designed to estimate the approximation error. The maximum allowable gain perturbation is also given. Then, the obtained results are extended to nonlinear systems in adaptive observer form with output uncertainty. Finally, some numerical simulations are offered to corroborate the theoretical results.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanical Engineering,Aerospace Engineering,Biomedical Engineering,General Chemical Engineering,Control and Systems Engineering

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