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A TP-LPV-LMI based control for Tumor Growth Inhibition ?

机译：基于TP-LPV-LMI的肿瘤生长抑制对照 ？

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The paper investigates the applicability of an advanced modern control method related to control of tumor growth under angiogenic inhibition. In order to describe the physiological process, a simple mathematical model was applied consisting of two states, the volume of the tumor and the inhibitor value. Extended Kalman Filter (EKF) was applied to estimate the unmeasurable state (inhibitor level). Linear Parameter Varying (LPV) models are used both at controller design (difference based control oriented LPV model) and EKF development (LPV model) level as well. We have used the Tensor Product (TP) model transformation accompanied by Linear Matrix Inequality (LMI) based optimization method in order to design a Parallel Distributed Compensator (PDC) kind TP-LPV-LMI controller considering additive disturbances (on both states) and sensor noise as well. Despite the assumed unfavorable effects the TP-LPV-LMI controller performed well achieving low final tumor volume and less totally injected inhibitor level.
机译：本文研究了在血管生成抑制下控制肿瘤生长的先进现代控制方法的适用性。为了描述生理过程，应用了由两个状态组成的简单数学模型，即肿瘤的体积和抑制剂的值。使用扩展卡尔曼滤波器（EKF）来估计不可测量的状态（抑制剂水平）。线性参数变量（LPV）模型也用于控制器设计（基于差异的面向控制的LPV模型）和EKF开发（LPV模型）级别。我们已经使用了基于Tensor Product（TP）模型的转换以及基于线性矩阵不等式（LMI）的优化方法，以便设计一种考虑了附加扰动（在两个状态下）和传感器的并行分布式补偿器（PDC）类型的TP-LPV-LMI控制器。噪音也是如此。尽管假定有不利的影响，TP-LPV-LMI控制器仍能很好地达到较低的最终肿瘤体积和较少的总注射抑制剂水平。

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