Fereydouneyan F, Zare A, Mehrshad N
Islamic Azad University, Gonabad Branch, Islamic Republic of Iran.
J Med Eng Technol. 2011 Jul;35(5):224-30. doi: 10.3109/03091902.2011.569050. Epub 2011 May 11.
In this paper a closed-loop control algorithm for blood glucose regulation in type 1 diabetic patients is proposed by using the Mamdani-type fuzzy method. Because of the presence of high-pass proportional derivatives in fuzzy designing, optimal values are applied for two inputs and one output membership functions in order to prevent the fluctuations due to derivatives in fuzzy design. Therefore, 19 values which are related to membership functions of the two inputs and one output are obtained by using a genetic algorithm (GA). The new model, termed the Augmented Minimal Model (AMM), is used in simulations. This controller is capable of stabilizing the blood glucose concentration at a normoglycaemic level of 90 mg dl(-1). The operation of the controller under various situations including multiple meal disturbances, and noise due to inaccurate effects of measuring blood glucose level are considered. Uncertainties in the meal disturbance function and variations of model parameters were also taken into consideration in simulations and the controller was found to be robust to such uncertainties.
本文提出了一种基于Mamdani型模糊方法的1型糖尿病患者血糖调节闭环控制算法。由于在模糊设计中存在高通比例导数，为防止模糊设计中导数引起的波动，对两个输入和一个输出隶属函数应用了最优值。因此，通过遗传算法（GA）获得了与两个输入和一个输出的隶属函数相关的19个值。新模型称为增强最小模型（AMM），用于仿真。该控制器能够将血糖浓度稳定在90mg dl(-1)的正常血糖水平。考虑了控制器在各种情况下的运行，包括多餐干扰以及由于血糖水平测量不准确而产生的噪声。在仿真中还考虑了餐食干扰函数的不确定性和模型参数的变化，发现该控制器对这些不确定性具有鲁棒性。
