Iterative learning feedback control for linear parabolic distributed parameter systems with multiple collocated piecewise observation

  • Yaqiang Liu
  • , Zongze Wu
  • , Jialun Lai
  • , Zhigang Ren
  • , Shengli Xie

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

This paper presents a novel iterative learning feedback control method for linear parabolic distributed parameter systems with multiple collocated piecewise observation. Multiple actuators and sensors distributed at the same position of the spatial domain are utilized to perform collocated piecewise control and measurement operations. The advantage of the proposed method is that it combines the iterative learning algorithm and feedback technique. Not only can it use the iterative learning algorithm to track the desired output trajectory, but also the feedback control approach can be utilized to achieve real-time online update. By utilizing integration by parts, triangle inequality, mean value theorem for integrals and Gronwall lemma, two sufficient conditions based on the inequality constraints for the convergence analysis of the tracking error system are presented. Some simulation experiments are provided to prove the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)1407-1426
Number of pages20
JournalJournal of the Franklin Institute
Volume359
Issue number4
DOIs
StatePublished - Mar 2022
Externally publishedYes

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