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Generalized predictive control insulin infusion amount calculating method based on adaptive reference curve strategy

A generalized predictive control and reference curve technology, applied in adaptive control, flow control, pressure infusion, etc., can solve problems such as difficult to achieve control effect

Inactive Publication Date: 2019-06-25
GUANGDONG FOOD & DRUG VOCATIONAL COLLEGE +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, its disadvantage is that the selection and construction of the model is often based on the physiological model of the patient's glucose metabolism, and the parameters need to be set with reference to clinical medical experience.
Although the model itself often has the ability of rolling optimization, once the model construction deviates, it is often difficult to achieve the expected control effect

Method used

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  • Generalized predictive control insulin infusion amount calculating method based on adaptive reference curve strategy
  • Generalized predictive control insulin infusion amount calculating method based on adaptive reference curve strategy
  • Generalized predictive control insulin infusion amount calculating method based on adaptive reference curve strategy

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0102] Such as figure 1 As shown, a generalized predictive control insulin infusion calculation method based on the adaptive reference curve strategy includes the following steps:

[0103] S1: According to the current blood sugar value, the predicted value of future blood sugar changes is obtained through the CARIMA model;

[0104] Through the CARIMA model and the Diophantine equation, the following equation is obtained:

[0105] y(k+j)=G j (z -1 )Δu(k+j-1)+F j (z -1 )y(k)(j=1,2...n)

[0106]In the formula, y(k) represents the blood glucose level at time k; y(k+j) represents the predicted value of blood glucose level j steps ahead at time k; Δu(k+j-1) represents the blood glucose level of the insulin pump at time k Control input increment; n represents the maximum prediction length; G j (z -1 ) represents the weight coefficient of the control input increment of the insulin pump at time k; F j (z -1 ) represents the weight coefficient of the blood sugar value;

[010...

Embodiment 2

[0140] Such as figure 1 As shown, a generalized predictive control insulin infusion calculation method based on the adaptive reference curve strategy includes the following steps:

[0141] S1: According to the current blood sugar value, the predicted value of future blood sugar changes is obtained through the CARIMA model;

[0142] Through the CARIMA model and the Diophantine equation, the following equation is obtained:

[0143] y(k+j)=G j (z -1 )Δu(k+j-1)+F j (z -1 )y(k)(j=1,2...n)

[0144] In the formula, y(k) represents the blood glucose level at time k; y(k+j) represents the predicted value of blood glucose level j steps ahead at time k; Δu(k+j-1) represents the blood glucose level of the insulin pump at time k Control input increment; n represents the maximum prediction length; G j (z -1 ) represents the weight coefficient of the control input increment of the insulin pump at time k; F j (z -1 ) represents the weight coefficient of the blood sugar value;

[01...

Embodiment 3

[0178] Such as figure 1 As shown, a generalized predictive control insulin infusion calculation method based on the adaptive reference curve strategy includes the following steps:

[0179] S1: According to the current blood sugar value, the predicted value of future blood sugar changes is obtained through the CARIMA model;

[0180] Through the CARIMA model and the Diophantine equation, the following equation is obtained:

[0181] y(k+j)=G j (z -1 )Δu(k+J-1)+F j (z -1 )y(k)(j=1,2...n)

[0182] In the formula, y(k) represents the blood glucose level at time k; y(k+j) represents the predicted value of blood glucose level j steps ahead at time k; Δu(k+j-1) represents the blood glucose level of the insulin pump at time k Control input increment; n represents the maximum prediction length; G j (z- 1 ) represents the weight coefficient of the control input increment of the insulin pump at time k; F j (z -1 ) represents the weight coefficient of the blood sugar value;

[01...

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Abstract

The invention discloses a generalized predictive control insulin infusion amount calculating method based on an adaptive reference curve strategy. The method includes utilizing real-time monitored human blood glucose data to predict future blood glucose change by using a CARIMA model, and then adopting the minimum variance to control and track the adaptive reference curve and calculate the infusion rate of an insulin pump in real time. The infusion is performed to reduce the blood glucose fluctuation of the human body and control the blood glucose in a predetermined target interval. Compared with the existing generalized predictive control algorithm, the adaptive reference curve strategy adopted can generate the reference curve suitable for different patients according to the blood glucosefluctuations of the patients to achieve control of the infusion rate of the insulin pump.

Description

technical field [0001] The present invention relates to the field of insulin pump infusion volume estimation, and more specifically, relates to a generalized predictive control insulin infusion volume calculation method based on an adaptive reference curve strategy. Background technique [0002] The existing insulin infusion control algorithm includes proportional calculus control algorithm, fuzzy control algorithm and model control algorithm and so on. [0003] Proportional Integral Derivative (PID) control is a relatively mature and widely used industrial control algorithm. The design of the insulin pump based on the PID algorithm has been realized by the Steil team of Medtronic MiniMed. Its main design idea is: the three components of the PID algorithm, the proportional, differential and integral components, respectively simulate the physiological transmission process of insulin secreted by human β cells. Among them, the linear proportional component corresponds to the i...

Claims

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Application Information

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IPC IPC(8): A61M5/142A61M5/168G05B13/04
Inventor 金浩宇刘文平余丽玲陈婷
Owner GUANGDONG FOOD & DRUG VOCATIONAL COLLEGE
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