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Extending Affine Control Policies to Hybrid Systems: Robust Control of a DC-DC Buck Converter


R. Vujanic, M. Schmitt, J. Warrington, M. Morari

European Control Conference (ECC), Zurich, Switzerland, pp. 1523-1528

Robust model predictive control has been used to determine sequences of inputs to dynamical systems that maximize a certain objective under uncertain dynamics or constraints. These sequences also ensure that hard state and input constraints are satisfied for any realization of the uncertainty. Performing an optimization over open loop control inputs in such circumstances is well known to lead to conservative input choices, leading to poor performance or even a failure to find a feasible input sequence. However, this conservativeness can be reduced by including recourse in the problem formulation. For linear systems with bounded disturbances, optimization over control laws that are affine in the disturbance measurements has emerged as a valid trade-off between performance and computational expense. In this paper we extend the idea of affine recourse to hybrid systems, and propose a new control approach that chooses integer decision variables over the control horizon in conjunction with continuous decision variables that are subject to recourse. Using the example of a buck power converter, we illustrate the efficacy of our approach in comparison to an implementation of affine control policies based on a linearized model.


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% Autogenerated BibTeX entry
@InProceedings { VujEtal:2013:IFA_4345,
    author={R. Vujanic and M. Schmitt and J. Warrington and M. Morari},
    title={{Extending Affine Control Policies to Hybrid Systems: Robust
	  Control of a DC-DC Buck Converter}},
    booktitle={European Control Conference (ECC)},
    address={Zurich, Switzerland},
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