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Direct Model Reference Adaptive Control of Periodic Slow Time-Varying Systems with Disturbance Input

  • Zhuolin Tan
  • , Xiaochen Xie*
  • , Jiantai Huang
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen
  • Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics

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

Abstract

This paper investigates the direct model reference adaptive control (MRAC) of periodic systems with slow time-varying dynamics and disturbance input. It is necessary to approximate the periodic slow time-varying system as a periodic piecewise linear system for MRAC. Based on the stability criteria of the periodic piecewise linear reference system,a new sufficient condition in terms of linear matrix inequalities (LMIs) is established to obtain the Lyapunov matrices and design the adaptive update law for the state feedback controller gains. Different from previous studies, where asymptotic tracking was possible only in the presence of a common Lyapunov function for the reference models, the asymptotic tracking in this work is achieved through a periodic time-varying Lyapunov matrix function. A numerical example validates the proposed MRAC scheme, and the effectiveness of the modified approach is discussed.

Original languageEnglish
Title of host publicationProceedings of the 43rd Chinese Control Conference, CCC 2024
EditorsJing Na, Jian Sun
PublisherIEEE Computer Society
Pages2492-2497
Number of pages6
ISBN (Electronic)9789887581581
DOIs
StatePublished - 2024
Externally publishedYes
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

  • Model Reference Adaptive Control
  • Periodic Piecewise Linear System
  • Periodic Slow Time-Varying System

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