Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.


Explicit MPC for LPV systems


Th. Besselmann, J. Löfberg, M. Morari

IEEE Conference on Decision and Control, Cancun, Mexico

In this paper we demonstrate how one can reformulate the MPC problem for LPV systems to a series of mpLPs by a closed-loop minimax MPC algorithm based on dynamic programming. A relaxation technique is employed to reformulate constraints which are polynomial in the scheduling parameters to parameter-independent constraints. The algorithm allows the computation of explicit control laws for linear parameter-varying systems and enables the controller to exploit information about the scheduling parameter. This improves the control performance compared to a standard robust approach where no uncertainty knowledge is used, while keeping the benefits of fast online computations. The off-line computational burden is similar to what is required for computing explicit control laws for uncertain or nominal LTI systems. The proposed control strategy is applied to an example to compare the complexity of the resulting explicit control law to the robust controller.


Type of Publication:


M. Morari

File Download:

Request a copy of this publication.
(Uses JavaScript)
% Autogenerated BibTeX entry
@InProceedings { BesL_f:2008:IFA_3084,
    author={Th. Besselmann and J. L{\"o}fberg and M. Morari},
    title={{Explicit MPC for LPV systems}},
    booktitle={IEEE Conference on Decision and Control},
    address={Cancun, Mexico},
Permanent link