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.


Bilevel programming for analysis of low-complexity control of linear systems with constraints


H. Manum, C.N. Jones, J. Löfberg, M. Morari, S. Skogestad

Conference on Decision and Control (CDC)

In this paper we use bilevel programming to find the maximum difference between a reference controller and a low-complexity controller in terms of the infinity- norm difference of their control laws. A nominal MPC for linear systems with constraints, and a robust MPC for linear systems with bounded additive noise are considered as reference controllers. For possible low-complexity controllers we discuss partial enumeration (PE), Voronoi/closest point, triangulation, linear controller with saturation, and others. A small difference in the norm between a low-complexity controller and a robust MPC may be used to guarantee closed-loop stability of the low-complexity controller and indicate that the behaviour or performance of the low-complexity controller will be similar to that of the reference one. We further discuss how bilevel programming may be used for closed-loop analysis of model reduction.


Type of Publication:


File Download:

Request a copy of this publication.
(Uses JavaScript)
% Autogenerated BibTeX entry
@InProceedings { ManEtal:2009:IFA_3459,
    author={H. Manum and C.N. Jones and J. L{\"o}fberg and M. Morari and S.
    title={{Bilevel programming for analysis of low-complexity control
	  of linear systems with constraints}},
    booktitle={Conference on Decision and Control (CDC)},
Permanent link