96 research outputs found

    Tumor Growth Control by TP-LPV-LMI Based Controller

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    Control of tumor growth by modern control methodologies

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    Linear Matrix Inequality based Control of Tumor Growth

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    Tensor Product based modeling of Tumor Growth

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    Robust H∞ controller design for T1DM based on relaxed LMI conditions

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    The aim of this research is to introduce an advanced controller design method which utilizes the Linear Parameter Variable (LPV) and Linear Matrix Inequality (LMI) theorems in order to control a given physiological model related to Diabetes Mellitus (DM). The developed approach is applied on a modified version of the so-called Minimal Model describes Type 1 DM condition. Due to the applied LPV-LMI conditions the resulting controller uses state feedback kind control rule. Further, robust and optimal control requirements have been included during the declaration of LMI rules allowing the formalization of complex requirements. The resulting control structure is robust from the considered disturbances points of view. During the validation we have found that the controller was able to handle highly unfavorable loads beside satisfying the predefined requirements
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