Distributed model predictive control

Many systems such as complex manufacturing, distribution networks, or process plants are often composed by multiple networked subsystems, with many embedded sensors and actuators. They are characterized by complex dynamics and mutual influences such that local control decisions made by single units have long-range effects throughout the system. This results in a very large number of problems that must be tackled for the design of an overall control system achieving the operating requirements in an optimal manner. When considering a control problem for a large-scale networked system, using model predictive control (MPC) in a centralized fashion may be considered impractical and unsuitable because of the computational burden, scalability issues, and communication bandwidth limitations, all of which make online, real-time centralized control unfeasible. It is also inflexible against changes of network structure and the limitation of information exchange between different agents who might be in control of local subsystems. To deal with these limitations, distributed MPC (DMPC) has been proposed for control of such large-scale systems, by decomposing the overall system into small subsystems. This special issue is devoted to DMPC, which is an emerging topic for scientific research. There are many open issues and several DMPC methods that have been proposed for different problem setups. The goal of this issue is to provide a state-of-the-art snapshot of the development of DMPC methods and applications. To that purpose, papers focusing on new methods and applications are welcome, including, but not limited to, some of the following topics:

  • Communication and coordination strategies

  • Control performance

  • Efficient methods and algorithms

  • Applications

  • Computational complexity

  • Robustness and reliability problems

  • Communication bandwidth limitations

Papers written or co-authored by researchers from the industry are encouraged, as well as papers involving either real data or detailed and realistic simulations. All submissions will be reviewed following the standard procedures of the journal, and acceptance will be limited to papers requiring only moderate revision.

Submission Details:

Prospective authors are requested to submit their manuscript online by 30 June 2013, to http://mc.manuscriptcentral.com/ocam-wiley (follow the instructions under ‘Author Centre’ and select manuscript type ‘Distributed Model Predictive Control’, when submitting). It would be helpful if you could inform the guest editors in advance of your intention to submit a paper.

For further information, please contact the guest editors.

Guest Editors for the Special Issue:

  • Prof. Eduardo F. Camacho

  • Systems Engineering and Automatic Control

  • University of Seville

  • Seville, Spain

  • Email: efcamacho@us.es

  • Prof. Carlos Bordons

  • Systems Engineering and Automatic Control

  • University of Seville

  • Seville, Spain

  • Email: bordons@us.es