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Game approach to distributed model predictive control

Game approach to distributed model predictive control

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  • Author(s): L. Giovanini 1
    • View affiliations
    • Affiliations: 1: National Council for Scientific and Technological Research and the Centre for Signals, Systems and Computational Intelligence, Faculty of Engineering and Water Sciences, Universidad Nacional del Litoral, Santa Fe, Argentina
  • Source: Volume 5, Issue 15, 13 October 2011, p. 1729 – 1739
    DOI:  10.1049/iet-cta.2010.0634 , Print ISSN 1751-8644, Online ISSN 1751-8652
© The Institution of Engineering and Technology
Published

This study introduces a framework for distributed model predictive control (MPC) based on dynamic games, where centralised and decentralised control algorithms can be viewed as dynamical games with coupled control sets. The original optimisation problem is decomposed into smaller coupled optimisation problems in a distributed structure, which is solved iteratively. Then, the resulting dynamic game is analysed using the theory of potential games to derive the properties of the resulting algorithms. This sheds new light on the properties of existing MPC algorithms and allows us to establish a unified framework to analyse them. The control problem of a heat-exchanger network (HEN) is used to illustrate the effectiveness, practicality and limitations of the proposed framework.

Inspec keywords: game theory; distributed control; decentralised control; optimisation; predictive control; heat exchangers

Other keywords: decentralised control algorithms; HEN; optimisation; dynamic games; heat-exchanger network; game approach; distributed model predictive control

Subjects: Multivariable control systems; Game theory; Optimal control; Optimisation techniques; Control of heat systems

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