A mixed-integer programming approach to networked control systems

Guofeng Zhang, Xiang Chen, Tongwen Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

This paper studies the problem of controller design for networked control systems regulated by a network data transmission protocol proposed in [50]. In this framework, the plant is first formulated as a mixed logical dynamical (MLD) system, then model predictive control (MPC) based on the mixed-integer programming is adopted to design a controller to guarantee certain control performance. It is shown that the solvability of the finite-horizon MPC is not equivalent to that of the infinite-horizon MPC, which is normally true for most existing MPC methods. The non-convexity feature of this type of networked control systems rules out explicit piecewise affine controllers that are designable for linear convex control systems. Notwithstanding these difficulties, controller design is still feasible due to the special nature of the data transmission strategy, i.e., only a small number of logic values are involved. Furthermore, control of higher-order systems and tracking of more complicated signals can be readily dealt with using this new approach. Two examples are presented to illustrate the strength of the proposed approach.
Original languageEnglish
Pages (from-to)590-611
Number of pages22
JournalInternational Journal of Numerical Analysis and Modeling
Volume5
Issue number4
Publication statusPublished - 9 Jul 2008
Externally publishedYes

Keywords

  • Hybrid systems
  • Mixed logical dynamical systems
  • Mixed-integer programming
  • Model predictive control
  • Networked control systems
  • Non-convexity

ASJC Scopus subject areas

  • Numerical Analysis

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