Model Predictive Control for Linear Systems under Relaxed Constraints

Saša V. Raković*, Sixing Zhang, Haidi Sun, Yuanqing Xia

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

This article considers model predictive control (MPC) for linear systems under relaxed constraints. The main novelty of our proposal is the introduction, and an adequate use, of the terminal dynamics of the slack variable associated with relaxed constraints. The proposed MPC under relaxed constraints retains computational efficiency of the traditional MPC, while it guarantees positive invariance and exponential stability over an enlarged domain of attraction. The design method is also illustrated in a step-by-step manner by an academic example.

Original languageEnglish
Pages (from-to)369-376
Number of pages8
JournalIEEE Transactions on Automatic Control
Volume68
Issue number1
DOIs
Publication statusPublished - 1 Jan 2023

Keywords

  • Linear systems
  • model predictive control
  • relaxed constraints

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