Citation
A. Abate, L. El Ghaoui. "Robust Model Predictive Control through Adjustable Variables: An Application to Path Planning". Proc. 43rd IEEE Conference on Decision and Control, The Bahamas, Dec. 2004, 2004.

Abstract
Robustness in Model Predictive Control (MPC) is the main focus of this work. After a definition of the conceptual framework and of the problem's setting, we will analyze how a technique developed for studying robustness in Convex Optimization can be applied to address the problem of robustness in the MPC problem. Therefore, exploiting this relationship between Control and Optimization, we will tackle robustness issues for the first setting through methods developed in the second framework. Proofs for our results are included. As an application of this Robust MPC result, we shall consider a Path Planning problem and discuss some simulations thereabout.

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• RobMPC_AARC.pdf · application/pdf · 164 kbytes

• HTML

  A. Abate, L. El Ghaoui. <a
  href="http://chess.eecs.berkeley.edu/pubs/105.html"
  >Robust Model Predictive Control through Adjustable
  Variables: An Application to Path Planning</a>, Proc.
  43rd IEEE Conference on Decision and Control, The Bahamas,
  Dec. 2004, 2004.

• Plain text

  A. Abate, L. El Ghaoui. "Robust Model Predictive
  Control through Adjustable Variables: An Application to Path
  Planning". Proc. 43rd IEEE Conference on Decision and
  Control, The Bahamas, Dec. 2004, 2004.

• BibTeX

  @inproceedings{AbateElGhaoui04_RobustModelPredictiveControlThroughAdjustableVariables,
      author = {A. Abate and L. El Ghaoui},
      title = {Robust Model Predictive Control through Adjustable
                Variables: An Application to Path Planning},
      booktitle = {Proc. 43rd IEEE Conference on Decision and
                Control, The Bahamas, Dec. 2004},
      year = {2004},
      abstract = {Robustness in Model Predictive Control (MPC) is
                the main focus of this work. After a definition of
                the conceptual framework and of the problem's
                setting, we will analyze how a technique developed
                for studying robustness in Convex Optimization can
                be applied to address the problem of robustness in
                the MPC problem. Therefore, exploiting this
                relationship between Control and Optimization, we
                will tackle robustness issues for the first
                setting through methods developed in the second
                framework. Proofs for our results are included. As
                an application of this Robust MPC result, we shall
                consider a Path Planning problem and discuss some
                simulations thereabout.},
      URL = {http://chess.eecs.berkeley.edu/pubs/105.html}
  }
  

Posted by Alessandro Abate on 15 May 2006.
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