Predefined-Time Adaptive Parameter Estimation for Nonlinear Systems

Jiangchao Song*, Xuemei Ren*, Jing Na, Dongdong Zheng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper examines a strategy for estimating parameters in nonlinear systems with unknown parameters, featuring predefined-time convergence. A new predefined-time stability criterion is proposed, offering a least upper bound on convergence time and enabling accurate calculation of actual convergence time. Additionally, the parameter estimation error is extracted using a specially designed auxiliary matrix. To mitigate the auxiliary matrix's impact on parameter estimation, an inverse matrix is developed. Consequently, a novel adaptive law with a predefined-time convergence characteristic is formulated to guarantee zero convergence of parameter errors within a predefined-time.

Original languageEnglish
Title of host publicationProceedings of the 43rd Chinese Control Conference, CCC 2024
EditorsJing Na, Jian Sun
PublisherIEEE Computer Society
Pages1354-1359
Number of pages6
ISBN (Electronic)9789887581581
DOIs
Publication statusPublished - 2024
Event43rd Chinese Control Conference, CCC 2024 - Kunming, China
Duration: 28 Jul 202431 Jul 2024

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference43rd Chinese Control Conference, CCC 2024
Country/TerritoryChina
CityKunming
Period28/07/2431/07/24

Keywords

  • Parameter estimation
  • nonlinear systems
  • predefined-time convergence

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