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.

A contribution to the identification in fuzzy-logic control

1990 ◽  
Vol 55 (4) ◽  
pp. 951-963 ◽  
Author(s):  
Josef Vrba ◽  
Ywetta Purová
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Automatic Generation ◽  
Linguistic Variable ◽  
Fuzzy Subset ◽  
Input Output ◽  
Logic Control ◽  
Correlation Tables

A linguistic identification of a system controlled by a fuzzy-logic controller is presented. The information about the behaviour of the system, concentrated in time-series, is analyzed from the point of its description by linguistic variable and fuzzy subset as its quantifier. The partial input/output relation and its strength is expressed by a sort of correlation tables and coefficients. The principles of automatic generation of model statements are presented as well.

Comparison of a Fuzzy Logic Controller With a P + D Control Law

1989 ◽  
Vol 111 (2) ◽  
pp. 128-137 ◽  
Author(s):  
S. Daley ◽  
K. F. Gill
Keyword(s):  
Fuzzy Logic ◽  
Attitude Control ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Good Control ◽  
Control Law ◽  
Dynamic Coupling ◽  
Process Knowledge ◽  
Logic Control ◽  
Limited Process

A study is described that compares the performance of a self-organizing fuzzy logic control law (SOC) with that of the more traditional P + D algorithm. The multivariate problem used for the investigation is the attitude control of a flexible satellite that has significant dynamic coupling of the axes. It is demonstrated that the SOC can provide good control, requires limited process knowledge and compares favorably with the P + D algorithm.

scholarly journals DC Motor Speed Control Using Mamdani Fuzzy Logic Based on Microcontroller

Jurnal Teknik ◽  
2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Sumardi Sadi
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Motor Speed ◽  
Logic Control ◽  
Control Command ◽  
Arduino Uno

DC motors are included in the category of motor types that are most widely used both in industrial environments, household appliances to children's toys. The development of control technology has also made many advances from conventional control to automatic control to intelligent control. Fuzzy logic is used as a control system, because this control process is relatively easy and flexible to design without involving complex mathematical models of the system to be controlled. The purpose of this research is to study and apply the fuzzy mamdani logic method to the Arduino uno microcontroller, to control the speed of a DC motor and to control the speed of the fan. The research method used is an experimental method. Global testing is divided into three, namely sensor testing, Pulse Width Modulation (PWM) testing and Mamdani fuzzy logic control testing. The fuzzy controller output is a control command given to the DC motor. In this DC motor control system using the Mamdani method and the control system is designed using two inputs in the form of Error and Delta Error. The two inputs will be processed by the fuzzy logic controller (FLC) to get the output value in the form of a PWM signal to control the DC motor. The results of this study indicate that the fuzzy logic control system with the Arduino uno microcontroller can control the rotational speed of the DC motor as desired.

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.  

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