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Constrained model predictive control for time-varying delay systems: Application to an active car suspension

  • Sofiane Bououden
  • , Mohammed Chadli*
  • , Lixian Zhang
  • , Ting Yang
  • *Corresponding author for this work
  • Abbès Laghrour University of Khenchala
  • Université de Picardie Jules Verne
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

This study investigates the problem of robust model predictive control (RMPC) for active suspension systems with time-varying delays and input constraints. The uncertainty is of convex polytopic type. Based on the Lyapunov-Krasovskii functional method, sufficient stability conditions of the time-varying delays systems are derived by linear matrix inequalities (LMIs) terms. At each time set, a feasible state feedback is obtained by minimizing an upper bound of the ‘worst-case’ quadratic objective function over an infinite horizon subject to constraints on inputs. Finally, a quarter-vehicle model is exploited to demonstrate the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)51-58
Number of pages8
JournalInternational Journal of Control, Automation and Systems
Volume14
Issue number1
DOIs
StatePublished - 1 Feb 2016

Keywords

  • Active suspension systems
  • LMIs constraints
  • input constraints
  • model predictive control
  • structured uncertainty
  • time-varying delays

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