Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 560702, 17 pages
http://dx.doi.org/10.1155/2015/560702
Research Article

Time-Varying Scheme for Noncentralized Model Predictive Control of Large-Scale Systems

1Section of Railway Engineering, Delft University of Technology, Stevinweg 1, 2628 CN Delft, Netherlands
2Institut de Robòtica i Informàtica Industrial (CSIC-UPC), Universitat Politècnica de Catalunya (UPC), Carrer Llorens i Artigas 4-6, 08028 Barcelona, Spain
3Departamento de Ingeniería de Sistemas y Automática, University of Seville, Camino de los Descubrimientos s/n, 41092 Seville, Spain
4Delft Center for Systems and Control, Delft University of Technology, Mekelweg 2, 2628 CD Delft, Netherlands

Received 23 June 2015; Revised 17 August 2015; Accepted 19 August 2015

Academic Editor: Qingling Zhang

Copyright © 2015 Alfredo Núñez et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. R. R. Negenborn, P.-J. van Overloop, T. Keviczky, and B. De Schutter, “Distributed model predictive control of irrigation canals,” Networks and Heterogeneous Media, vol. 4, no. 2, pp. 359–380, 2009. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  2. R. R. Negenborn, B. De Schutter, and J. Hellendoorn, “Multi-agent model predictive control for transportation networks: serial versus parallel schemes,” Engineering Applications of Artificial Intelligence, vol. 21, no. 3, pp. 353–366, 2008. View at Publisher · View at Google Scholar · View at Scopus
  3. C. Ocampo-Martinez, V. Puig, G. Cembrano, and J. Quevedo, “Application of predictive control strategies to the management of complex networks in the urban water cycle [Applications of Control],” IEEE Control Systems Magazine, vol. 33, no. 1, pp. 15–41, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  4. J. M. Maestre, D. M. de la Peña, E. F. Camacho, and T. Alamo, “Distributed model predictive control based on agent negotiation,” Journal of Process Control, vol. 21, no. 5, pp. 685–697, 2011. View at Publisher · View at Google Scholar
  5. R. Scattolini, “Architectures for distributed and hierarchical model predictive control: a review,” Journal of Process Control, vol. 19, no. 5, pp. 723–731, 2009. View at Publisher · View at Google Scholar · View at Scopus
  6. R. R. Negenborn and J. M. Maestre, “Distributed model predictive control: an overview and roadmap of future research opportunities,” IEEE Control Systems, vol. 34, no. 4, pp. 87–97, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  7. P. Trodden and A. Richards, “Adaptive cooperation in robust distributed model predictive control,” in Proceedings of the IEEE Control Applications & Intelligent Control (CCA-ISIC '09), pp. 896–901, IEEE, Saint Petersburg, Russia, July 2009. View at Publisher · View at Google Scholar
  8. M. Jilg and O. Stursberg, “Optimized distributed control and topology design for hierarchically interconnected systems,” in Proceedings of the 12th European Control Conference (ECC '13), pp. 4340–4346, Zurich, Switzerland, July 2013. View at Scopus
  9. T. Sadamoto, T. Ishizaki, and J.-I. Imura, “Hierarchical distributed control for networked linear systems,” in Proceedings of the 53rd IEEE Annual Conference on Decision and Control (CDC '14), pp. 2447–2452, IEEE, Los Angeles, Calif, USA, December 2014. View at Publisher · View at Google Scholar
  10. J. M. Maestre, D. M. de la Peña, A. J. Losada, E. Algaba, and E. F. Camacho, “A coalitional control scheme with applications to cooperative game theory,” Optimal Control Applications and Methods, vol. 35, no. 5, pp. 592–608, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  11. F. Fele, J. M. Maestre, S. M. Hashemy, D. Muñoz de la Peña, and E. F. Camacho, “Coalitional model predictive control of an irrigation canal,” Journal of Process Control, vol. 24, no. 4, pp. 314–325, 2014. View at Publisher · View at Google Scholar · View at Scopus
  12. F. Muros, J. Maestre, E. Algaba, T. Alamo, and E. Camacho, “An iterative design method for coalitional control networks with constraints on the shapley value,” in Proceedings of the 19th IFAC World Congress, pp. 1188–1193, Cape Town, South Africa, August 2014.
  13. A. Núñez, C. Ocampo-Martinez, B. De Schutter, F. Valencia, J. D. López, and J. Espinosa, “A multiobjective-based switching topology for hierarchical model predictive control applied to a hydro-power valley,” in Proceedings of the 3rd IFAC Conference on Intelligent Control and Automation Science (ICONS '13), pp. 534–539, Chengdu, China, September 2013. View at Publisher · View at Google Scholar · View at Scopus
  14. A. Anand and L. Samavedham, “Optimizing the communication topology in a coordinated model predictive control architecture,” in Proceedings of the 5th International Symposium on Advanced Control of Industrial Processes, pp. 318–323, Hiroshima, Japan, May 2014.
  15. C. Ocampo-Martinez, S. Bovo, and V. Puig, “Partitioning approach oriented to the decentralised predictive control of large-scale systems,” Journal of Process Control, vol. 21, no. 5, pp. 775–786, 2011. View at Publisher · View at Google Scholar · View at Scopus
  16. M. E. Sezer and D. D. Šiljak, “Nested ε-decompositions and clustering of complex systems,” Automatica, vol. 22, no. 3, pp. 321–331, 1986. View at Publisher · View at Google Scholar · View at MathSciNet
  17. J. Anderson, Y.-C. Chang, and A. Papachristodoulou, “Model decomposition and reduction tools for large-scale networks in systems biology,” Automatica, vol. 47, no. 6, pp. 1165–1174, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  18. S. Kamelian and K. Salahshoor, “A novel graph-based partitioning algorithm for large-scale dynamical systems,” International Journal of Systems Science, vol. 46, no. 2, pp. 227–245, 2015. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  19. H. Li and Y. Shi, “Distributed receding horizon control of large-scale nonlinear systems: handling communication delays and disturbances,” Automatica, vol. 50, no. 4, pp. 1264–1271, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  20. C. Ocampo-Martinez, V. Puig, J. M. Grosso, and S. Montes-de-Oca, “Multi-layer decentralized MPC of large-scale networked systems,” in Distributed Model Predictive Control Made Easy, vol. 69 of Intelligent Systems, Control and Automation: Science and Engineering, chapter 31, pp. 495–515, Springer, Dordrecht, The Netherlands, 2014. View at Publisher · View at Google Scholar
  21. J. Grosso, On model predictive control for economic and robust operation of generalised flow-based networks [Ph.D. thesis], Universitat Politècnica de Catalunya—BarcelonaTech, Barcelona, Spain, 2015.
  22. R. S. Sanchez-Pena and F. D. Bianchi, “Model selection: from LTI to switched-LPV,” in Proceedings of the American Control Conference (ACC '12), pp. 1561–1566, Montreal, Canada, June 2012. View at Scopus
  23. J. Maciejowski, Predictive Control with Constraints, Prentice Hall, London, UK, 2002.
  24. J. M. Maestre and R. R. Negenborn, Eds., Distributed Model Predictive Control Made Easy, vol. 69 of Intelligent Systems, Control and Automation: Science and Engineering, Springer, Dordrecht, The Netherlands, 2014. View at Publisher · View at Google Scholar
  25. P. Frasca, H. Ishii, C. Ravazzi, and R. Tempo, “Distributed randomized algorithms for opinion formation, centrality computation and power systems estimation: a tutorial overview,” European Journal of Control, vol. 24, no. 1, pp. 2–13, 2015. View at Publisher · View at Google Scholar · View at MathSciNet
  26. Z. Li, Z. Duan, G. Chen, and L. Huang, “Consensus of multiagent systems and synchronization of complex networks: a unified viewpoint,” IEEE Transactions on Circuits and Systems. I. Regular Papers, vol. 57, no. 1, pp. 213–224, 2010. View at Publisher · View at Google Scholar · View at MathSciNet
  27. O. Demir and J. Lunze, “Optimal and event-based networked control of physically interconnected systems and multi-agent systems,” International Journal of Control, vol. 87, no. 1, pp. 169–185, 2014. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  28. R. Schuh and J. Lunze, “Desing of the communication structure of a selforganizing networked controller for heterogeneous agents,” in Proceedings of the European Control Conference, pp. 2199–2206, Linz, Austria, July 2015.
  29. I. Alvarado, D. Limon, D. M. de la Peña et al., “A comparative analysis of distributed MPC techniques applied to the HD-MPC four-tank benchmark,” Journal of Process Control, vol. 21, no. 5, pp. 800–815, 2011. View at Publisher · View at Google Scholar · View at Scopus
  30. J. Maestre, M. Ridao, A. Kozma et al., “A comparison of distributed MPC schemes on a hydro-power plant benchmark,” Optimal Control Applications and Methods, vol. 36, no. 3, pp. 306–332, 2015. View at Publisher · View at Google Scholar
  31. J. M. Maestre, F. Muros, F. Fele, and E. F. Camacho, “An assessment of coalitional control in water systems,” in Proceedings of the 14th European Control Conference (ECC '15), Linz, Austria, July 2015.