Iterative Proportional-Integral Interval Estimation of Linear Discrete-Time Systems

Mouquan Shen, Tu Zhang, Ju H. Park, Qing Guo Wang, Li Wei Li

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

An iterative proportional-integral interval estimation strategy for linear discrete-time systems is investigated in this article. A sequence iterative proportional-integral observer is built on system output and unknown disturbance iterative estimation. With the help of a structure separation technique, a sufficient condition in terms of linear matrix inequality is proposed to make the observer error system be asymptotically stable. The boundary reachability of the observer error system is analyzed via zonotope. The zonotope-based iterative algorithms, with and without the output integral, are built to generate estimated state intervals. Compared with the existing result, the proposed algorithms render tighter estimation intervals illustrated by a simulation study.

Original languageEnglish
Pages (from-to)4249-4256
Number of pages8
JournalIEEE Transactions on Automatic Control
Volume68
Issue number7
DOIs
StatePublished - 1 Jul 2023

Keywords

  • Linear systems
  • robust control
  • state estimation

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