Optimization-Based Design for Data-Driven Control of SISO Nonaffine Nonlinear Systems

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

Abstract

For the adaptive tracking of nonaffine nonlinear systems, the unknown nonlinear dynamics is regarded as one of the essential factors that may hinder the effective controller establishment and the tracking precision improvement. To tackle this difficulty for a class of single-input single-output (SISO) nonaffine nonlinear systems, we develop an optimization-based design method for data-driven control to achieve the desired tracking objective in the presence of the time-varying reference trajectory. It is shown that the proposed data-driven controller can render the tracking error to strictly converge, regardless of the SISO unknown nonlinear dynamics. In addition, thanks to a novel grouping-based contraction mapping method and properties of non-negative matrices, the boundedness of the I/O sequence is established. Simulations are implemented to verify that the proposed data-driven controller can realize the anticipated tracking performance for nonlinear systems.

Original languageEnglish
Title of host publicationProceedings of the 41st Chinese Control Conference, CCC 2022
EditorsZhijun Li, Jian Sun
PublisherIEEE Computer Society
Pages5645-5650
Number of pages6
ISBN (Electronic)9789887581536
DOIs
StatePublished - 2022
Event41st Chinese Control Conference, CCC 2022 - Hefei, China
Duration: 25 Jul 202227 Jul 2022

Publication series

NameChinese Control Conference, CCC
Volume2022-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference41st Chinese Control Conference, CCC 2022
Country/TerritoryChina
CityHefei
Period25/07/2227/07/22

Keywords

  • Data-driven control
  • Grouping-based analysis method
  • Non-negative matrix
  • Nonaffine nonlinear system

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