A study on different configurations of fractional order fuzzy logic controller scheme for robotic manipulator using NSGA-II

2018 ◽  
Author(s):  
Richa Sharma ◽  
Deepak Joshi ◽  
Prerna Gaur
Keyword(s):  
Fuzzy Logic ◽  
Fractional Order ◽  
Fuzzy Logic Controller ◽  
Robotic Manipulator ◽  
Nsga Ii

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

2021 ◽  
Vol 54 (3) ◽  
pp. 381-394
Author(s):  
Salah Benzian ◽  
Aissa Ameur ◽  
Aissa Rebai
Keyword(s):  
Fuzzy Logic ◽  
Blood Glucose ◽  
Blood Sugar ◽  
Fractional Order ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Heuristic Algorithms ◽  
Control Unit ◽  
Scientific Paper ◽  
Invasive Weed

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.

scholarly journals A Variable Fractional Order Fuzzy Logic Control Based MPPT Technique for Improving Energy Conversion Efficiency of Thermoelectric Power Generator

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4531
Author(s):  
N. Kanagaraj ◽  
Hegazy Rezk ◽  
Mohamed R. Gomaa
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Energy Conversion ◽  
Fractional Order ◽  
Conversion Efficiency ◽  
Fuzzy Logic Controller ◽  
Energy Conversion Efficiency ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Power Point

Thermoelectric generation technology is considered to be one of the viable methods to convert waste heat energy directly into electricity. The utilization of this technology has been impeded due to low energy conversion efficiency. This paper aims to improve the energy conversion efficiency of the thermoelectric generator (TEG) model with a novel maximum power point tracking (MPPT) technique. A variable fractional order fuzzy logic controller (VFOFLC)-based MPPT technique is proposed in the present work in which the operating point of the TEG is moved quickly towards an optimal position to increase the energy harvesting. The fraction order term α, introduced in the MPPT algorithm, will expand or contract the input domain of the fuzzy logic controller (FLC to shorten the tracking time and maintain a steady-state output around the maximum power point (MPP). The performance of the proposed MPPT technique was verified with the TEG model by simulation using MATLAB /SIMULINK software. Then, the overall performance of the VFOFLC-based MPPT technique was analyzed and compared with Perturb and observe (P&O) and incremental resistance (INR)-based MPPT techniques. The obtained results confirm that the proposed MPPT technique can improve the energy conversion efficiency of the TEG by harvesting the maximum power within a shorter time and maintaining a steady-state output when compared to other techniques.

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