• DocumentCode
    2457109
  • Title

    Model Predictive Control: Design and implementation using MATLAB (T-3)

  • Author

    Liuping Wang

  • Author_Institution
    RMIT University, Australia
  • fYear
    2009
  • fDate
    10-12 June 2009
  • Firstpage
    25
  • Lastpage
    26
  • Abstract
    Model Predictive Control (MPC) has a long history in the field of control engineering. It is one of the few areas that have received on-going interest from researchers in both the industrial and academic communities. Three major aspects of model predictive control make the design methodology attractive to both engineers and academics. The first aspect is the design formulation, which uses a completely multivariable system framework where the performance parameters of the multivariable control system are related to the engineering aspects of the system; hence, they can be understood and ‘tuned’ by engineers. The second aspect is the ability of method to handle both ‘soft’ constraints and hard constraints in a multivariable control framework. This is particularly attractive to industry where tight profit margins and limits on the process operation are inevitably present. The third aspect is the ability to perform process on-line optimization.
  • Keywords
    Control engineering; Design engineering; Design methodology; Electrical equipment industry; History; MATLAB; MIMO; Mathematical model; Predictive control; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2009. ACC '09.
  • Conference_Location
    St. Louis, MO, USA
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4244-4523-3
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2009.5159781
  • Filename
    5159781