Distributed MPC: A Noncooperative Approach Based on Robustness Concepts

  • G. BettiEmail author
  • M. Farina
  • R. Scattolini
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 69)


The Distributed Predictive Control (DPC) algorithm presented in this chapter has been designed for control of an overall system made by linear discrete-time dynamically interconnected subsystems. It consists of a non-cooperative, non-iterative algorithm where a neighbor-to-neighbor transmission protocol is needed. The DPC algorithm enjoys the following properties: (i) state and input constraints can be considered; (ii) convergence is guaranteed; (iii) it is not necessary for each subsystem to know the dynamical models of the other subsystems; (iv) the transmission of information is limited.


Reference Trajectory Output Feedback Control Prediction Horizon Terminal Constraint Dynamic Neighbor 
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.



The authors would like to thank Giancarlo Ferrari Trecate, Stefano Riverso and Davide Melzi for fruitful discussions.


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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Dipartimento di Elettronica e InformazionePolitecnico di MilanoMilanItaly

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