Skip to main content
SpringerLink
Log in
Book cover

Distributed Model Predictive Control Made Easy pp 585–600Cite as

Cooperative MPC with Guaranteed Exponential Stability

  • Chapter
  • First Online:

Part of the book series: Intelligent Systems, Control and Automation: Science and Engineering ((ISCA,volume 69))

Abstract

In this chapter, a cooperative distributed MPC is presented. The main features of this control strategy are: constraints satisfaction; cooperation between agents to achieve an agreement; closed-loop stability that is always ensured, even in the case of just one iteration; achieved control actions that are plantwide Pareto optimal and equivalent to the centralized solution; Pareto optimality is achieved also in case of coupled constraints; a coordination layer is not needed. It is proved that cooperative MPC is a particular case of suboptimal MPC; exponential stability is then proved, based on exponential stability of suboptimal centralized MPC.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    A FACTS is a device employed to manipulate the effective impedance of a tie-line and control power flow between two interconnected control areas.

References

  1. D.P. Bertsekas, J.N. Tsitsiklis, Parallel and Distributed Computation (Athena Scientific, Belmont, 1997)

    Google Scholar 

  2. S. Boyd, L. Vandenberghe. Convex Optimization. Cambridge University Press, 2006

    Google Scholar 

  3. A. Ferramosca, D. Limon, I. Alvarado, E. F. Camacho. Cooperative distributed MPC for tracking. Automatica, 2013 in press

    Google Scholar 

  4. R.D. Gudi, J.B. Rawlings, Identification for decentralized model predictive control. AIChE J. 52(6), 2198–2210 (2006)

    Article  Google Scholar 

  5. J. B. Rawlings, D. Q. Mayne. Model Predictive Control: Theory and Design, 1st edition. Nob-Hill Publishing, 2009

    Google Scholar 

  6. R. Scattolini, Architectures for distributed and hierarchical model predictive control - a review. J. Process Control. 19(5), 723–731 (2009)

    Article  Google Scholar 

  7. P.O.M. Scokaert, D.Q. Mayne, J.B. Rawlings, Suboptimal model predictive control (feasibility implies stability). IEEE Trans. Autom. Control. 44(3), 648–654 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  8. B.T. Stewart, A.N. Venkat, J.B. Rawlings, S.J. Wright, G. Pannocchia, Cooperative distributed model predictive control. Syst. Control. Lett. 59, 460–469 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  9. B. T. Stewart. Plantwide Cooperative Distributed Model Predictive Control. Ph.D. thesis, University of Wisconsin, Madison, 2010

    Google Scholar 

  10. B. T. Stewart, J. B. Rawlings, S. J. Wright, Hierarchical cooperative distributed model predictive control In Proceedings of the American Control Conference, Baltimore, June 2010

    Google Scholar 

  11. A. N. Venkat. Distributed Model Predictive Control: Theory and Applications. Ph.D. thesis, Univeristy of Wisconsin, Madison, October 2006

    Google Scholar 

  12. A.N. Venkat, I.A. Hiskens, J.B. Rawlings, S.J. Wright, Distributed MPC strategies with application to power system automatic generation control. IEEE Ctl. Sys. Tech. 16(6), 1192–1206 (2008)

    Article  Google Scholar 

  13. A. N. Venkat, J. B. Rawlings, S. J. Wright. Distributed model predictive control of large-scale systems. In Assessment and Future Directions of Nonlinear Model Predictive Control, Springer, 2007,pp. 591–605

    Google Scholar 

Download references

Acknowledgments

The author would like to thank Professor James B. Rawlings and Dr. Brett T. Stewart for helpful discussions and comments, as well as for material provided for the writing of this chapter.

Author information

Authors and Affiliations

  1. Institute of Technological Development for the Chemical Industry (INTEC), CONICET-Universidad Nacional del Litoral (UNL), Santa Fe, Argentina

    A. Ferramosca

Authors
  1. A. Ferramosca
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. Ferramosca .

Editor information

Editors and Affiliations

  1. Systems Engineering and Automation Dept, University of Seville, Seville, Spain

    José M. Maestre

  2. Dept of Marine & Transport Technology, Delft University of Technology, Delft, The Netherlands

    Rudy R. Negenborn

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Ferramosca, A. (2014). Cooperative MPC with Guaranteed Exponential Stability. In: Maestre, J., Negenborn, R. (eds) Distributed Model Predictive Control Made Easy. Intelligent Systems, Control and Automation: Science and Engineering, vol 69. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7006-5_36

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-7006-5_36

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-7005-8

  • Online ISBN: 978-94-007-7006-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation