Event-based iterative learning predictive control under two-dimensional framework

Guangchen Zhang*, Han Gao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we pay attention to event-based iterative learning predictive control for the iterative learning system affected by network delays under two-dimensional (2D) framework. First, the well-posed iterative learning predictive system is introduced to depict the lost data induced by network delays. Subsequently, the prediction-batch–based event-triggered protocol is formulated to help alleviate the adverse influence of network delays. Based on these preparations, we attempt to solve iterative learning predictive control by virtue of the 2D system theorem. To this end, the 2D Roesser-type predictive control model is carried out to describe the iterative learning predictive system, and then, the predictive control problem is considered for such 2D Roesser predictive model. The corresponding stability criteria and controller design are achieved, which also realize the tracking control of the iterative learning system. To conclude this paper, the examples are examined to illustrate the effectiveness of the proposed approach and controller design.

Original languageEnglish
Pages (from-to)2534-2543
Number of pages10
JournalTransactions of the Institute of Measurement and Control
Volume46
Issue number13
DOIs
Publication statusPublished - Sept 2024

Keywords

  • 2D Roesser-type model
  • Predictive control
  • event-triggered protocol
  • iterative learning control
  • network delays
  • tracking control

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