Blood glucose control using an ABC algorithm-based fuzzy-PID controller (original) (raw)

This paper presents Fuzzy-PID (FPID) control scheme for a blood glucose control of type 1 diabetic subjects. A new metaheuristic Cuckoo Search Algorithm (CSA) is utilized to optimize the gains of FPID controller. CSA provides fast convergence and is capable of handling global optimization of continuous nonlinear systems. The proposed controller is an amalgamation of fuzzy logic and optimization which may provide an efficient solution for complex problems like blood glucose control. The task is to maintain normal glucose levels in the shortest possible time with minimum insulin dose. The glucose control is achieved by tuning the PID (Proportional Integral Derivative) and FPID controller with the help of Genetic Algorithm and CSA for comparative analysis. The designed controllers are tested on Bergman minimal model to control the blood glucose level in the facets of parameter uncertainties, meal disturbances and sensor noise. The results reveal that the performance of CSA-FPID control...

In this paper a closed-loop control algorithm is developed for blood glucose regulation in type I diabetes mellitus patients. The control technique incorporates expert knowledge about treatment of disease by using Mamdani-type fuzzy logic controller to stabilize the blood glucose concentration in normoglycaemic level of 70 mg/dl. Controller performance is assessed in terms of its ability to reject the multiple meal disturbances resulting from food intake, on an averaged nonlinear patient model. Robustness of the controller is tested over a group of patients with model parameter varying considerably from the average model. In addition, proposed controller provides the possibility of more accurate control of blood glucose level in the patient in spite of uncertainty in model and measurement noise. Simulation results show the superiority of the proposed scheme in terms of robustness to uncertainty in comparison with other researches.

In this paper, an optimal PID-FLC (Proportional Integral Derivative Fuzzy Logic Controller) is proposed. The design of this system aims to control blood glucose elevation in type 1 diabetic patients. An automated system integrated with a miniaturized insulin infusion pump and a continuous biosensor that measures the glucose level has been developed recently to replace beta cells in the pancreas. The main contribution of the paper is that it introduces an automated insulin delivery system based on a parallel PID-FLC structure tuned with genetic algorithms. This control system was compared to an optimal PIFLC and PD-FLC as well as a reference model. The results revealed that the controllers could maintain the glucose level within a normal range. In addition, the performance of the PIFLC and the PID-FLC was very close to that of beta cells in normal individuals. So, they can be exploited prosperously as control systems to manage blood glucose concentrations in Type 1 diabetic patients. In addition, the PID-FLC saved the amount of the daily delivered insulin, while, its performance was approximately the same as that of the PI-FLC.