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Lyapunov-Based Distributed MPC Schemes: Sequential and Iterative Approaches

  • J. LiuEmail author
  • D. Muñoz de la Peña
  • P. D. Christofides
Chapter
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 69)

Abstract

In this chapter, we focus on two distributed MPC (DMPC) schemes for the control of large-scale nonlinear systems in which several distinct sets of manipulated inputs are used to regulate the system. In the first scheme, the distributed controllers use a one-directional communication strategy, are evaluated in sequence and each controller is evaluated once at each sampling time; in the second scheme, the distributed controllers utilize a bi-directional communication strategy, are evaluated in parallel and iterate to improve closed-loop performance. In the design of the distributed controllers, Lyapunov-based model predictive control techniques are used. To ensure the stability of the closed-loop system, each model predictive controller in both schemes incorporates a stability constraint which is based on a suitable Lyapunov-based controller. We review the properties of the two DMPC schemes from stability, performance, computational complexity points of view. Subsequently, we briefly discuss the applications of the DMPC schemes to chemical processes and renewable energy generation systems.

Keywords

Model Predictive Control Stability Constraint Model Predictive Controller Input Trajectory Energy Generation System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • J. Liu
    • 1
    Email author
  • D. Muñoz de la Peña
    • 2
  • P. D. Christofides
    • 3
  1. 1.Department of Chemical and Materials EngineeringUniversity of AlbertaEdmontonCanada
  2. 2.Departamento de Ingeniería de Sistemas y AutomáticaUniversidad de SevillaSevillaSpain
  3. 3.Department of Chemical and Biomolecular Engineering and Department of Electrical EngineeringUniversity of CaliforniaLos AngelesUSA

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