scholarly journals Power Factor Correction Using Fuzzy Logic Control

2014 ◽  
Vol 9 (1) ◽  
pp. 11-20 ◽  
Author(s):  
P. Kripakaran ◽  
◽  
J. Sathishkumar ◽  
R.Gopi Krishna
Keyword(s):  
Fuzzy Logic ◽  
Power Factor ◽  
Fuzzy Logic Control ◽  
Power Factor Correction ◽  
Logic Control

scholarly journals Power factor control of PV generators in local distribution networks using fuzzy logic concept

2018 ◽  
Vol 7 (2.28) ◽  
pp. 362
Author(s):  
Raed A. Shalwala
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Power Factor ◽  
Fuzzy Logic Control ◽  
Reactive Power ◽  
Distribution Network ◽  
Voltage Control ◽  
Distribution Networks ◽  
Voltage Regulation ◽  
Logic Control

One of the most important operational requirements for any electrical power network for both distribution and transmission level is voltage control. Many studies have been carried out to improve or develop new voltage control techniques to facilitate safe connection of distributed generation. In Saudi Arabia, due to environmental, economic and development perspectives, a wide integration of photovoltaic (PV) genera-tion in distribution network is expected in the near future. This development in the network may cause voltage regulation problems due to the interaction with the existing conventional control system. In a previous paper, a control system has been described using a fuzzy logic control to set the on-line tap changer for the primary substation. In this paper a new control system is proposed for controlling the power factor of individual PV invertors based on observed correlation between net active and reactive power at each connection. A fuzzy logic control has been designed to alter the power factor for the remote invertors from the secondary substation to keep the feeder voltage within the permissible limits. In order to confirm the validity of the proposed method, simulations are carried out for a realistic distribution network with real data for load and solar radiation. Results showing the performance of the new control method are presented and discussed.  

scholarly journals Performance Analysis of Power Electronic Distribution Transformer using Adaptive Pi-Fuzzy Logic Controller

2020 ◽  
Vol 8 (6) ◽  
pp. 3050-3054
Keyword(s):  
Fuzzy Logic ◽  
Power Factor ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Pi Controller ◽  
Power Electronic ◽  
Distribution Transformer ◽  
Logic Control ◽  
Electronic Distribution ◽  
Adaptive Fuzzy Logic

This paper enlightens the analysis of distributed transformer using novel controller. The transformer initiates power distribution by stepping up or down depends upon the need. In accordance with power quality issues, performance, dynamic response, power factor correction the normalized transformer is inconvenient. Replacing the uncertainties by introducing a power electronic distribution transformer (PET) with PI controlled adaptive fuzzy logic control (APIFC). Moreover the occurrence of breakdown voltage and stress in conventional method, this method becoming more popular. This transformer become sensitive to dealt with swell, sag, voltage regulation, open circuit and short circuit fault. The specified rectifier also does power factor correction. The strategic PI controller with adaptive fuzzy logic control technique is established to respond sudden change or variation occurs in load. The fuzzy logic controller (FLC) posses five set of rules and PI controller adapt with one among five set of rules. This makes the controller to adjust with variation and improves power quality. The simulation is carried out using MatLab-Simulink.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

Sign in / Sign up

Export Citation Format

Share Document