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Explicit MPC for systems with linear parameter-varying state transition matrix


Th. Besselmann, J. Löfberg, M. Morari

vol. AUT07-14

In this paper we propose a closed-loop minimax MPC algorithm based on dynamic programming, which allows the computation of explicit control laws for systems with a linear parameter-varying state transition matrix. This enables the controller to exploit parameter information to improve 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 case. An application to the controlled H´enon map follows to draw a comparison, in terms of complexity and control performance, with a controller based on a piecewise affine approximation, to investigate for which control tasks a parameter-varying model could be employed.


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(04)Technical Report

M. Morari

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% Autogenerated BibTeX entry
@TechReport { BesL_f:2007:IFA_3036,
    author={Th. Besselmann and J. L{\"o}fberg and M. Morari},
    title={{Explicit MPC for systems with linear parameter-varying
	  state transition matrix}},
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