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Distributed MPC of polytopic uncertain systems: handling quantised communication and packet dropouts

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  • Langwen Zhang
  • Jingcheng Wang
  • Bohui Wang

Abstract

In this paper, we study the distributed model predictive control (MPC) of polytopic uncertain systems with quantised communication and packet dropouts. The model of the whole plant is divided into a certain number of incomplete subsystems. Due to the nature of the distributed control structure, there is generally a lack of information about the state of the overall system. Each subsystem shares its information with neighbour subsystems via reliable connection. Distributed MPC controllers are designed for each subsystem by solving the linear matrix inequalities optimisation problem. The distributed state feedback laws are quantised and transmitted via communication network. An iterative algorithm is presented to make coordination among distributed state feedback laws. The communication is assumed to be affected by random packet dropouts in a representation of Bernoulli distributed white sequences with known conditional probabilities. A case study is carried out to demonstrate the effectiveness of the proposed distributed MPC technique.

Suggested Citation

  • Langwen Zhang & Jingcheng Wang & Bohui Wang, 2015. "Distributed MPC of polytopic uncertain systems: handling quantised communication and packet dropouts," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(13), pages 2393-2406, October.
    • Handle: RePEc:taf:tsysxx:v:46:y:2015:i:13:p:2393-2406
    DOI: 10.1080/00207721.2014.998748
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