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A dual approach for positive T-S fuzzy controller design and its application to cancer treatment under immunotherapy and chemotherapy

机译:正T-S模糊控制器设计的双重方法及其在免疫疗法和化学疗法治疗癌症中的应用

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This study proposes an effective positive control design strategy for cancer treatment by resorting to the combination of immunotherapy and chemotherapy. The treatment objective is to transfer the initial number of tumor cells and immune-competent cells from the malignant region into the region of benign growth where the immune system can inhibit tumor growth. In order to achieve this goal, a new modeling strategy is used that is based on Takagi-Sugeno. A Takagi-Sugeno fuzzy model is derived based on the Stepanova nonlinear model that enables a systematic design of the controller. Then, a positive Parallel Distributed Compensation controller is proposed based on a linear co-positive Lyapunov Function so that the tumor volume and administration of the chemotherapeutic and immunotherapeutic drugs is reduced, while the density of the immune-competent cells is reached to an acceptable level. Thanks to the proposed strategy, the entire control design is formulated as a Linear Programming problem. Finally, the simulation results show the effectiveness of the proposed control approach for the cancer treatment. (C) 2019 Elsevier Ltd. All rights reserved.
机译:这项研究提出了一种有效的阳性对照设计策略,通过采用免疫疗法和化学疗法相结合的方法来治疗癌症。治疗的目的是将肿瘤细胞和具有免疫功能的细胞的初始数量从恶性区域转移到良性生长区域,在该区域免疫系统可以抑制肿瘤的生长。为了实现此目标,使用了基于Takagi-Sugeno的新建模策略。基于Stepanova非线性模型导出了Takagi-Sugeno模糊模型,该模型可实现控制器的系统设计。然后,基于线性共阳性Lyapunov函数,提出了一种正并联分布补偿控制器,以减少肿瘤体积和化疗药物和免疫治疗药物的使用,同时使免疫功能细胞的密度达到可接受的水平。 。由于所提出的策略,整个控制设计被表述为线性规划问题。最后,仿真结果表明了所提出的控制方法对癌症治疗的有效性。 (C)2019 Elsevier Ltd.保留所有权利。

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