Design an Optimal Fractional Order PID Controller Based on New Algorithms and a Fuzzy Logic Controller to Regulate Type 1 Diabetes Patients

Abstract

Diabetes is one of the most important diseases that researchers have focused on in scientific research since the time, because of the seriousness of this disease if it is not properly dealt with, especially with the emergence of some global epidemics such as Corona Virus (COVID 19), as the pancreas is the organ responsible for regulating sugar in the blood by secreting the insulin enzyme, insulin is widely used to control blood sugar. Therefore, it is important that the required insulin value is constant and controlled. The aim of this study is to control the blood glucose value that is achieved as a desired value and to maintain it as a constant value using a proportional, integral, and derivative control unit (FOPID) fractional order of the control parameters. In this research, the new control unit is applied to Bergman's mathematical model as a non-linear and simple model that simulates the mechanism of the interaction of glucose and insulin in the blood, and based on this, a closed control loop was designed to regulate the level of blood sugar to be an automatic control of blood glucose using the measured data from Special sensor. The contribution in this scientific paper is to define the (FOPID) parameters according to the closed loop responses of the system, and these parameters were adjusted using new meta-heuristic algorithms including the Invasive Weed Optimization (IWO), the PSO Particle Swarm optimization, the Genetic Algorithm (GA), The bat optimization algorithm (BA) and (ACO). As a result, the results of the five modern algorithms were compared based on several criteria to find out which one was better using MATLAB / SIMULINK simulation. It was found that the IWO algorithm performs better than PSO. The simulation results of the closed-loop system of this controller at the time of settling, overshoot and control inputs indicate very positive results compared to previous results. In addition, a new method has been proposed which is to design a pump in the form of a valve to control insulin pumping by controlling it with the fuzzy logic control unit, which in turn, we obtained better results, compared to the results of other previous studies.

Enhancement of the Blood Glucose Level for Diabetic Patients Based on an Adaptive Auto-Tuned PID Controller via Meta-Heuristic Methods

“…As demonstrated in Table 7, we compared the simulation results of the suggested off-line adaptive The fractional order PID and the fuzzy logic controllers in [8] were built for the linear Bergman model and only for the first patient, using only five rules for the membership function and using the tryand-error method for obtaining the gain in the inputoutput fuzzy logic controller. Therefore, the controller generates a fast and non-optimal value of the insulin control action that leads to an overshoot in the response of the blood glucose level.…”

“…They used the Ziegler-Nichols (Z-N) tuning method to find the control parameters, which led to an overshoot in the response of the blood glucose of the patient because the Z-N tuning method is not suitable for exploring and exploiting the global extreme solution of the problem. Furthermore, the authors in [8] employed the fractional order PID controller and the fuzzy logic controller for regulating the blood glucose level of a T1D patient, and they used many types of meta-heuristic algorithms for tuning the control gain parameters of the FOPID. However, the limitation of this work is that these controllers have been built for the linear Bergman model and only for one patient, and they used only five rules for the membership function, with a try-and-error method to obtain the gain in the input-output fuzzy logic controller.…”

“…Table 1 shows the parameters of the Bergman model equations that describe normal, first, second, and third patients as follows [8,10,17,18].…”

Optimization of Fractional Order PI Controller by PSO Algorithm Applied to a Grid-Connected Photovoltaic System

“…V qref = E q + V * q + ωL f I d (9) where: E d , E q the voltages of the common connection points to the grid; L f is the coupling inductance of the filter device. In recent years, researchers have been interested in a new design of the PID controller to be applied in many domains, especially control theories compared to classical PID controllers because of their advantages, which are to increase the performance of non-linear, dynamic systems and to be less sensitive to changes in system parameters [9,39].…”

“…Figure 6. PWM control strategy 3.2.1 Fractional order PID controllerIn recent years, researchers have been interested in a new design of the PID controller to be applied in many domains, especially control theories compared to classical PID controllers because of their advantages, which are to increase the performance of non-linear, dynamic systems and to be less sensitive to changes in system parameters[9,39].This control device is named fractional order PID (or FOP 𝐼 𝜆 𝐷 𝜇 ) and has been proposed by Podlunby since the 1990s[40]. In addition to the control parameters 𝐾 𝑝 , 𝐾 𝑖 and 𝐾 𝑑 of a classical PID controller, there are 𝜆 and 𝜇 , the fractional components of the integral and derivative parts respectively.Figure7illustrates the block diagram of the fractional order PID controller.…”