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Archana Balan

Bio: Archana Balan is an academic researcher from Indian Institute of Science. The author has an hindex of 1, co-authored 1 publications receiving 15 citations.

Papers
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Journal ArticleDOI
TL;DR: The design of control algorithms in the presence of noises and various other disturbances is discussed, which in turn introduces sensor noise in the measurement, thereby leading to model imperfection.

22 citations


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21 Jul 2011
TL;DR: In this article, the problem of the identification of single individual parameters in detailed dynamic models of glucose homeostasis is considered, and the optimal model-based design of experiment techniques are used to design a set of clinical tests that allow the model parameters to be estimated in a statistically sound way, while meeting constraints related to safety of the subject and ease of implementation.
Abstract: Type 1 diabetes mellitus is a disease affecting millions of people worldwide and causing the expenditure of millions of euros every year for health care. One of the most promising therapies derives from the use of an artificial pancreas, based on a control system able to maintain the normoglycaemia in the subject affected by diabetes. A dynamic simulation model of the glucose-insulin system can be useful in several circumstances for diabetes care, including testing of glucose sensors, insulin infusion algorithms, and decision support systems for diabetes. This paper considers the problem of the identification of single individual parameters in detailed dynamic models of glucose homeostasis. Optimal model-based design of experiment techniques are used to design a set of clinical tests that allow the model parameters to be estimated in a statistically sound way, while meeting constraints related to safety of the subject and ease of implementation. The model with the estimated set of parameters represents a specific subject and can thus be used for customized diabetes care solutions. Simulated results demonstrate how such an approach can improve the effectiveness of clinical tests and serve as a tool to devise safer and more efficient clinical protocols, thus providing a contribution to the development of an artificial pancreas.

32 citations

Journal ArticleDOI
TL;DR: An augmented subcutaneous model of type 1 diabetic patients (T1DP) is proposed first by estimating the model parameters with the aid of nonlinear least square method using the physiological data and a nonlinear adaptive controller is proposed to tackle two important issues of intra-patient variability and uncertain meal disturbance.

26 citations

Journal ArticleDOI
TL;DR: In this article, an energy-efficient, valveless piezoelectric pump is designed and simulated with different types of controllers and glucose-insulin models to keep the blood glucose level of Type 1 diabetes mellitus patients in the desired range.
Abstract: The objective of this work is to develop a closed-loop controlled insulin pump to keep the blood glucose level of Type 1 diabetes mellitus (T1DM) patients in the desired range. In contrast to the existing artificial pancreas systems with syringe pumps, an energy-efficient, valveless piezoelectric pump is designed and simulated with different types of controllers and glucose-insulin models. COMSOL Multiphysics is used for piezoelectric-fluid-structural coupled 3D finite element simulations of the pump. Then, a reduced-order model (ROM) is simulated in MATLAB/Simulink together with optimal and proportional-integral-derivative (PID) controllers and glucose–insulin models of Ackerman, Bergman, and Sorensen. Divergence angle, nozzle/diffuser diameters, lengths, chamber height, excitation voltage, and frequency are optimized with dimensional constraints to achieve a high net flow rate and low power consumption. A prototype is manufactured and experimented with different excitation frequencies. It is shown that the proposed system successfully controls the delivered insulin for all three glucose–insulin models.

23 citations

Journal ArticleDOI
28 Jul 2020
TL;DR: This paper presents a comprehensive survey about the fundamental components of the artificial pancreas (AP) system including insulin administration and delivery, glucose measurement (GM), and control strategies/algorithms used for type 1 diabetes mellitus (T1DM) treatment and control.
Abstract: This paper presents a comprehensive survey about the fundamental components of the artificial pancreas (AP) system including insulin administration and delivery, glucose measurement (GM), and control strategies/algorithms used for type 1 diabetes mellitus (T1DM) treatment and control. Our main focus is on the T1DM that emerges due to pancreas’s failure to produce sufficient insulin due to the loss of beta cells (β-cells). We discuss various insulin administration and delivery methods including physiological methods, open-loop, and closed-loop schemes. Furthermore, we report several factors such as hyperglycemia, hypoglycemia, and many other physical factors that need to be considered while infusing insulin in human body via AP systems. We discuss three prominent control algorithms including proportional-integral- derivative (PID), fuzzy logic, and model predictive, which have been clinically evaluated and have all shown promising results. In addition, linear and non-linear insulin infusion control schemes have been formally discussed. To the best of our knowledge, this is the first work which systematically covers recent developments in the AP components with a solid foundation for future studies in the T1DM field.

22 citations

Journal ArticleDOI
TL;DR: The results indicate that hypoglycemia and post-prandial hyperglycemia are significantly reduced in the presence of bounded parametric variability and uncertain exogenous meal disturbance.
Abstract: This paper deals with the design of robust observer based output feedback control law for the stabilisation of an uncertain nonlinear system and subsequently apply the developed method for the regulation of plasma glucose concentration in Type 1 diabetes (T1D) patients. The principal objective behind the proposed design is to deal with the issues of intra-patient parametric variation and non-availability of all state variables for measurement. The proposed control technique for the T1D patient model is based on the attractive ellipsoid method (AEM). The observer and controller conditions are obtained in terms of linear matrix inequality (LMI), thus allowing to compute easily both the observer and controller gains. The closed-loop response obtained using the designed controller avoids adverse situations of hypoglycemia and post-prandial hyperglycemia under uncertain conditions. Further to validate the robustness of the design, closed-loop simulations of random 200 virtual T1D patients considering parameters within the considered ranges are presented. The results indicate that hypoglycemia and post-prandial hyperglycemia are significantly reduced in the presence of bounded ( ± 30 % ) parametric variability and uncertain exogenous meal disturbance.

16 citations