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Model Predictive Control: A Multi-parametric Programming Approach

Author(s):

A. Bemporad, N.A Bozinis, V. Dua, M. Morari, E.N. Pistikopoulos
Conference/Journal:

European Symposium on Computer Aided Process Engineering, Florence, Italy, pp. 301-306
Abstract:

In this paper, linear model predictive control problems are formulated as multi-parametric quadratic programs, where the control variables are treated as optimization variables and the state variables as parameters. It is shown that the control variables are affine functions of the state variables and each of these affine functions is valid in a certain polyhedral region in the space of state variables. An approach for deriving the explicit expressions of all the affine functions and their corresponding polyhedral regions is presented. The key advantage of this approach is that the control actions are computed off-line: the on-line computation simply reduces to a function evaluation problem.

Further Information
Year:

2000
Type of Publication:

(01)Article
Supervisor:



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% Autogenerated BibTeX entry
@InProceedings { BemEtal:2000:IFA_88,
    author={A. Bemporad and N.A Bozinis and V. Dua and M. Morari and E.N.
	  Pistikopoulos},
    title={{Model Predictive Control: A Multi-parametric Programming
	  Approach}},
    booktitle={European Symposium on Computer Aided Process Engineering},
    pages={301--306},
    year={2000},
    address={Florence, Italy},
    month=may,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=88}
}
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