Stability analysis tool for tuning unconstrained decentralized model predicitive controllers

M. Vaccarini, S. Longhi, M.R. Katebi

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Abstract

Some processes are naturally suitable to be controlled in a decentralized framework: centralized control solutions are often infeasible in dealing with large scale plants and they are technologically prohibitive when the processes are too fast for the available computational resources. In these cases, the resulting control problem is usually split in many smaller subproblems and the global requirements are guaranteed by means of a proper coordination. The unconstrained decentralized case is here considered and a coordination strategy is proposed for improving the global control performances. This paper present a tool for setting up and tuning a nominally stable decentralized Model Predictive Controller. Numerical
examples are proposed for testing and validating the developed technique.
Original languageEnglish
Number of pages5
Publication statusPublished - 2006
EventInternational Control Conference 2006 - Glasgow, UK
Duration: 30 Aug 20061 Sep 2006
http://ukacc.group.shef.ac.uk/Control_Conferences/Control2006/icc2006.htm

Conference

ConferenceInternational Control Conference 2006
Abbreviated titleICC2006
CityGlasgow, UK
Period30/08/061/09/06
OtherThe Conference covers Methods, Technology, Applications and Education in Control Engineering. UKACC seeks to act as an effective link between the UK and the international control communities, and to provide a focus for International Federation of Automatic Control (IFAC) related activities. UKACC has three constituent members: The Institution of Engineering and Technology (IET), The Institute of Measurement and Control (IMC), and The Institution of Mechanical Engineers (IMechE).
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Keywords

  • decentralized control
  • optimal regulators
  • predictive control
  • stability analysis
  • communication networks

Cite this

Vaccarini, M., Longhi, S., & Katebi, M. R. (2006). Stability analysis tool for tuning unconstrained decentralized model predicitive controllers. Paper presented at International Control Conference 2006, Glasgow, UK, .