Fractional Order Sliding Mode Blood Glucose Control Using Functions Approximation Techniques

In this paper, based on function approximation techniques and sliding mode control strategy, a robust controller for blood glucose regulation is presented. Recently, there has been an increasing trend towards application of fractional order calculus in various fields. Healthcare of patients involved in diabetes mellitus is not exception and various researches have been carried out in this area. In order to design a robust controller, uncertainties should be estimated and compensated. Different estimators can be used for this purpose such as neural networks and fuzzy systems, due to their property of universal approximation. However, there are many tuning parameters in these estimators. Based on the orthogonal functions theorem, we can design other uncertainty estimators such as the Fourier series expansion and Legendre polynomials. Thus, in this paper, the Fourier series expansion is applied for uncertainty estimation in fractional order control of blood glucose. The efficiency of the proposed controller, i.e. robustness and high accuracy, in presence of physical disturbances like food intake and parametric uncertainties is verified via simulations.

Keywords:

Fractional calculus , function approximation techniques , blood glucose regulation)