Modeling and analysis of PID and Fuzzy Control For Blood Glucose-Insulin System

 

Presentation of DP-1

Guided By:Mr.J .A TalatiAssistant Professor,Dept. of Ins. Engineering,AITS, Rajkot.

Prepared By:Divya K NadarM.E. (Applied Instrumentation )Atmiya Inst. of Tech. & Sci., RajkotEnroll. No - 140030703013

SUBMITTED TO:GUJARAT TECHNOLOGICAL UNIVERSITY

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Flow of Presentation

Introduction Blood glucose insulin system Literature Review Problem statement Simulation of blood glucose model Proposed work References

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Abstract

Diabetes is a widespread disease in the western world today. Many researchers are working on methods for diagnosing and treating diabetes[1].

Normally the therapy is based on discrete insulin infusion that uses long time interval measurements. A continuous drug insulin is proposed to avoid the traditional discrete approaches by automating diabetes therapy and to deal with this kind of plant the controllers used : proportional integral derivative (PID), and fuzzy logic controllers (FLC).

A fully automated closed-loop insulin delivery system could potentially be the ultimate answer for blood glucose (BG) control in diabetic patients. This system can mimic the activity of a normal pancreas and is capable of maintaining physiological BG levels for insulin-dependent diabetic patients[2].

A tool used for this is mathematical models of the blood glucose and insulin

kinetics.A minimal model is can be described through derivation and simulations.

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The construction of the mathematical model describing the whole blood glucose system can be tried.

The main aim is to do mathematical modeling and then analyse the PID and fuzzy controller .

The numerical solution presents the complex situation of diabetic patients. Computer simulations are used to evaluate the effectiveness of the proposed work.

 

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Introduction

Scientists do not know exactly what causes type 1 diabetes, but they believe that a combination of genetic and environmental factors are to blame. Diabetes is an autoimmune disease.

This means that the immune system, which normally ignores healthy cells but destroys germs and foreign substances that could cause illness, mistakenly launches an attack on the body itself - in this case destroying insulin producing islet cells in the pancreas.

Scientists are developing external insulin which is fed in a certain rate according to maintain the glucose levels of 60-120 mg/dl.

The diabetes is classified as Type-1 and Type-2. In case of Type-1 the controlling of insulin is very difficult. For these patients regulation of blood glucose concentration is maintained by releasing the external insulin with insulin infusion device.

The insulin pump is a electro medical device which delivers insulin through narrow and flexible plastic tube that ends with a needle inserted just under the skin near the abdomen[1].

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Blood Glucose insulin system

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Figure 1.Block diagram of Glucose Insulin regulation system[2]

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Components of the system

Figure 2.Components of the system[3]

Literature Review

Paper – I

Marchetti, Gianni, Massimiliano Barolo, Lois Jovanovic, Howard Zisser, and Dale E. Seborg. "An improved PID switching control strategy for type 1 diabetes." Biomedical Engineering, IEEE Transactions on 55, no. 3 (2008): 857-865[4]

This paper mainly focuses on the control strategy that is PID for the blood glucose control using a physiologic model of Hovarka et al.

The authors demonstrated the results of the proposed control strategy of PID supports the realistic conditions of meal, measurement noise ,changes in insulin sensitivity .

The feature of the control is that it superiors for both meal challenges with the poor CHO (carbohydrates) estimates and insulin sensitivity change.

Tuning is done and an improved PID strategy was demonstrated for a variety of the circumstances to be robust ,carried by simulations ,considering a diabetic patient.

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Literature Review

Paper – IILi, Chengwei, and Ruiqiang Hu. "Fuzzy-PID control for the regulation of blood glucose in diabetes." In Intelligent Systems, 2009. GCIS'09. WRI Global Congress on, vol. 2, pp. 170-174. IEEE, 2009[5].

In this paper the author has two control algorithms Fuzzy-PID control and classical

PID control method for the insulin to inject to diabetic patient.

A comparison is made between PID fuzzy and classical PID by simulations result, which will be evident for the theoretical analysis.

The mathematical model used of blood glucose regulation for simulation is taken as “minimal model” Bergman et al.

These model will relate glucose and insulin with expressions. The results of both the algorithms shows Fuzzy-PID performed well compared to the classical PID which is valid for the glucose regulation.

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Literature Review

Paper –III

Maleki, Ali, and Arezou Geramipour. "Continuous control of blood glucose in TIDM using fuzzy logic controller in insulin pump: A simulation study." In Control, Instrumentation and Automation (ICCIA), 2011 2nd International Conference on, pp. 122-127. IEEE, 2011.[6]

The aim of the author is to design a controller i.e fuzzy logic controller and shows the robustness by testing it and this is done by a compared with PID controller and the results are shown by taking various diabetic patients and the FLC response is stable in presence of uncertainty in system parameters which will vary from patient to patient and PID is also tuned but FLC could reduce the blood glucose level of each patient in terms of hyperglycemia and hypoglycemia prevention and physiological model taken Bergman minimal .

The control of fuzzy is only for the insulin pump to inject the insulin the patient and its not for the glucose.

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Paper –IVSasi, Ahmed Y. Ben, and Mahmud A. Elmalki. "A fuzzy controller for blood glucose-insulin system." Journal of Signal and Information Processing 4, no. 02 (2013): 111.

Literature Review

A controller receives the difference between the glucose set point (desired BG) and the glucose reading, and uses this information to continuously adjust the rate of insulin delivery.

This closed-loop control is very similar to the function that is performed by a healthy human pancreas.

There is a continuous drug infusion closed-loop control system was proposed to avoid the traditional discrete approaches by automating diabetes therapy.

Therefore proportional integral derivative (PID), and fuzzy logic controllers (FLC). Simulation results have illustrated that the fuzzy logic controller outperformed the PID controller.

These results were based on serious disturbances to glucose, such as exercise, delay or noise in glucose sensor and nutrition mixed meal absorption at meal time.

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Paper – 5

Li, P., Yu, L., Guo, L., Dong, J., Hu, J., & Fang, Q. (2012, July). PID control of glucose concentration in subjects with type 1 diabetes based on a simplified model: An in silico trial. In Intelligent Control and Automation (WCICA), 2012 10th World Congress on (pp. 5051-5055). IEEE[8].

Literature Review

This paper shows ,accurate insulin-glucose metabolism model is essential to the development of a closed loop control system for an Artificial Pancreas System(APS) which regulates glucose concentration for T1DM patients.

By using the proposed simplified model, much fewer parameters are required to estimate from clinical data.

The PID closed-loop in silico simulation results show that the plasma glucose concentration can decrease much than the open-loop control and the risk of hyperglycemia and hypoglycemia reduced a lot.

PID controller is designed to maintain normoglycemia (90mg/dl) in subjects with T1DM.

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Problem statement

The problem is that the PID controller calculates insulin infusion rate to the diabetic patient released by the pump into the tissue t can endanger the life of a diabetic patients as the mostly the empirical models is used for the modeling without much consideration of physiological parameters .

The considered model could be modified with more number of parameters to do mathematical modeling and then analyse with the PID and fuzzy controller and to minimize the overshoot of the controller.

The numerical solution presents the complex situation of diabetic patients.

Computer simulations are used to evaluate the effectiveness of the proposed work.

 

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Compartment blood glucose model

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.

Figure 4.3 Compartmental diagram of the glucose and insulin systems in a diabetic patient[8]

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Modeling of blood glucose model

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Figure 4.4 Simulink model of diabetic patient (Sorensen)

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Figure 4.5 Glucose submodel of diabetic patient

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Figure 4.5 Insulin model of diabetic patient

Project work

Mathematical model to describe the glucose-insulin dynamics of a T1DM patient and modified model accordingly.

The implementation of an insulin administration strategy, also denoted as a controller that is PID and fuzzy and different tuning techniques to enhance the performance in order to get the proper insulin to the diabetic patient.

A set of performance metrics to evaluate the performance of the AP such that different insulin administration strategies can be compared .

To develop a user friendly software in MATLAB that implements physiological model of the glucose-insulin system during meals would be tried.

The graphical interface makes its use extremely easy for investigators without specific expertise on modeling.

 

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References

[1]http://www.joslin.org/diabetesresearch/type_1_diabetes_research.html [2]Srinivas, P., & Rao, P. D. P. CLOSED LOOP MODEL FOR GLUCOSE INSULIN

REGULATION SYSTEM USING LABVIEW.[3] http://medical-dictionary.thefreedictionary.com/insulin+pumpy[4]

[5] Li, Chengwei, and Ruiqiang Hu. "Fuzzy-PID control for the regulation of blood glucose in diabetes." In Intelligent Systems, 2009. GCIS'09. WRI Global Congress on, vol. 2, pp. 170-174. IEEE, 2009.

[6]  Maleki, Ali, and Arezou Geramipour. "Continuous control of blood glucose in TIDM using fuzzy logic controller in insulin pump: A simulation study." In Control, Instrumentation and Automation (ICCIA), 2011 2nd International Conference on, pp. 122-127. IEEE, 2011.

[7] Sasi, Ahmed Y. Ben, and Mahmud A. Elmalki. "A fuzzy controller for blood glucose-insulin system." Journal of Signal and Information Processing 4, no. 02 (2013): 111.

[8] Li, P., Yu, L., Guo, L., Dong, J., Hu, J., & Fang, Q. (2012, July). PID control of glucose concentration in subjects with type 1 diabetes based on a simplified model: An in silico trial. In Intelligent Control and Automation (WCICA), 2012 10th World Congress on (pp. 5051-5055). IEEE[8].correction according to chicago format

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Thank you

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