scholarly journals Power System Stabilization By Fuzzy Set Theory Based Control Of SMES

1970 ◽  
Vol 6 (2) ◽  
pp. 33-41 ◽  
Author(s):  
Md Rafiqul Islam Sheikh ◽  
Rion Takahashi ◽  
Junji Tamura
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Power System ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Magnetic Energy ◽  
Dynamic Performance ◽  
Superior Performance ◽  
Logic Control

At present fuzzy logic control is receiving increasing emphasis in process control applications. The paper describes the application of fuzzy logic control in a power system that uses a 12- pulse bridge converter associated with Superconductive Magnetic Energy Storage (SMES) unit. The fuzzy control is used in both the frequency and voltage control loops, replacing the conventional control method. The control algorithms have been developed in detail and simulation results are presented. These results clearly indicate the superior performance of fuzzy control during the dynamic period of energy transfer between the power system and SMES unit. Keywords: Fuzzy logic controller; power system dynamic performance; SMES unit. DOI: http://dx.doi.org/10.3329/diujst.v6i2.9343 DIUJST 2011; 6(2): 33-41

scholarly journals Voltage and Frequency Control of Balanced/Unbalanced Distribution System Using the SMES System in the Presence of Wind Energy

Electricity ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 205-224
Author(s):  
Hossam S. Salama ◽  
Istvan Vokony
Keyword(s):  
Fuzzy Logic ◽  
Wind Energy ◽  
Distribution System ◽  
Fuzzy Logic Control ◽  
High Performance ◽  
Control Method ◽  
Magnetic Energy ◽  
Frequency Control ◽  
Control Technique ◽  
Logic Control

This paper presents an effective solution to overcome the problem caused by intermittent energy sources that are connected to a balanced/unbalanced distribution system using a superconducting magnetic energy storage (SMES) system by mitigating the voltage and frequency fluctuations during wind gusts. The fuzzy logic control technique (FLC) is used with SMES to improve the voltage and frequency. A squirrel cage induction generator (SCIG) is applied as the wind energy generator. The IEEE 33-bus distribution system is used to validate the proposed method. Buses 18 33 are the weakest points in this system; thus, the wind and SMES systems are connected to the system at these buses. We used MATLAB/Simulink to simulate the performance of the IEEE 33-bus system (balanced/unbalanced) considering the SMES, wind system, and fuzzy logic control (FLC). The simulation results show the high performance of the proposed control method to alleviate the voltage and frequency fluctuation and achieve the power leveling strategy of the studied system.

scholarly journals An Optimized Fuzzy Logic Control Model Based on a Strategy for the Learning of Membership Functions in an Indoor Environment

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 132 ◽  
Author(s):  
Muhammad Fayaz ◽  
Israr Ullah ◽  
DoHyeun Kim
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Environmental Temperature ◽  
Fuzzy Inference ◽  
Control Method ◽  
Learning Algorithm ◽  
Membership Functions ◽  
Inference Method ◽  
Logic Control

The Mamdani fuzzy inference method is one of the most important fuzzy logic control (FLC) techniques and has several applications in different fields. Despite its applications, the Mamdani fuzzy inference method has some core issues which still require solutions. The most critical issue is the selection of accurate shape and boundaries of membership functions (MFs) in the universe of discourse. In this work, we introduced a methodology called learning to control (LtC) to resolve the problem. The proposed methodology consisted of two main modules, namely, a control algorithm (CA) module and a learning algorithm (LA) module. In the CA module, the Mamdani FLC method has been used, whereas, in the LA module, we have used the artificial neural network (ANN) algorithm. Inputs into the ANN were the error difference between environmental temperature and the required temperature. The output of the ANN was the MF set to the FLC. Inputs into the fuzzy logic controller (FLC) were the error difference between environmental temperature and required temperature (D), and the output was the required power for the fan actuator. The purpose of the ANN was to tune the MFs of the FLC to improve its efficiency. The proposed learning-to-control method along with the conventional fuzzy logic controller method was applied to the data to evaluate the model’s performance. The results indicate that the proposed model’s performance is far better than that of conventional fuzzy logic techniques.

Experimental Investigation on Swash Plate Axial Piston Pumps With Conical Cylinder Blocks Using Fuzzy Logic Control

2002 ◽  
Author(s):  
M. K. Bahr Khalil ◽  
J. Svoboda ◽  
R. B. Bhat
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Real Time Control ◽  
Axial Piston Pumps ◽  
Time Control ◽  
Logic Control ◽  
Swash Plate ◽  
Axial Piston

Analytical studies on the dynamic performance of variable displacement swash plate axial piston pumps show that the pump performance can significantly improved by replacing the conventional PD process controller with fuzzy logic controller. Electrically controlled, constant power regulated, swash plate pumps with conical cylinder blocks have been recently extensively studied. Comparative study has been carried out to compare the pump dynamic performance when the conventional PD process controller is replaced by a proposed fuzzy logic one. The study reveals some superior performance characteristics when fuzzy logic controller is used. In the present study an experimental setup is built to measure the dynamic performance of a typical 9-piston pump that has conical shaped cylinder block. The pump is of 40 cc/rev geometrical size, type A4VSO, that is manufactured by Rexroth. The experimental setup consists of a hydraulic test bed interfaced with real time control and data acquisition system. The setup is used firstly for testing the pump static characteristics. Subsequently, the setup is used to measure the time response of the pump, which is equipped with the conventional PD controller, to the stepwise changes in the load pressure. Pump model verification is then discussed based on the comparison between the theoretical and experimental results. The pump is afterwards interfaced with real time control software for prototyping the proposed fuzzy logic controller that replaces the currently used PD one. With the fuzzy logic control, measuring the pump time response under the same loading conditions is repeated. Experimental results are presented, compared with the analytical findings and discussed.

scholarly journals Evaluation of the High Performance Indirect Field Oriented Controlled Dual Induction Motor Drive Fed by a Single Inverter using Type-2 Fuzzy Logic Control

2020 ◽  
Vol 10 (5) ◽  
pp. 6301-6308
Author(s):  
A. Bounab ◽  
A. Chaiba ◽  
S. Belkacem
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Control ◽  
High Performance ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Voltage Source ◽  
Switching Frequency ◽  
Logic Control

In this paper, a high-performance indirect field-oriented controlled dual Induction Motor (IM) drive fed by a single inverter using type-2 fuzzy logic control will be presented. At first, the mathematical model of the IM is implemented in the d-q reference frame. Then, the speed control of the Dual Induction Motor (DIM) operating in parallel configuration with Indirect Field Oriented Control (IFOC) using PI and type-2 Fuzzy Logic Controller (T2-FLC) will be presented. For the control of this system, a DC supply and a Space Vector Pulse Width Modulation (SVPWM) voltage source inverter are introduced with constant switching frequency. Also, the performance of T2-FLC, which is based on the IFOC, is tested and compared to those achieved using the PI controller. The simulation results demonstrate that the T2-FLC is more robust, efficient, and has superior dynamic performance for traction system applications.

Fuzzy Logic Control

1993 ◽  
pp. 20-40 ◽  
Author(s):  
Marzuki Khalid ◽  
Sigeru Omatu
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Bath Temperature ◽  
Water Bath ◽  
Temperature Control System ◽  
Clear Understanding ◽  
Logic Control ◽  
Fuzzy Logic Theory

Although fuzzy logic theory was proposed about three decades ago, it is only until recently that fuzzy control technology has been successfully applied to many industrial systems and domestic appliances. Much of these developments is mainly due to a better understanding of the concept of fuzzy logic, its simplicity of implementation, and its feasibility in hardware development. This article intends to provide a simple but clear understanding on the concept of fuzzy logic and its application to control systems (therefore not intended for those who have already understood the basic principles of fuzzy logic control). A simulation example is given on the development and operation of a fuzzy logic controller for a multi-variable water bath temperature control system. C-pseudocodes are given in the Appendices to clarify the water bath fuzzy control algorithms.

Fuzzy Logic Control of the Marine Permanent Magnet Synchronous Propulsion Motor with Direct Torque Control System

2014 ◽  
Vol 889-890 ◽  
pp. 920-924
Author(s):  
Chun Yang Zhang ◽  
Jin Nan Zhang ◽  
Cai Qin Sun
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Permanent Magnet ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Direct Torque Control ◽  
Torque Control ◽  
New Method ◽  
Logic Control

As to the ripple problem of the direct torque control system of permanent magnet synchronous motor, this paper present a new method based on the fuzzy logic control. The new method replaces the traditional hysteresis torque controller by a fuzzy logic controller to realize the low ripple effect of the torque and the flux linkage. Also this paper modeling and simulate the new control system using the FIS toolbox provided by the Matlab/Simulink software, and the simulation results shows that the fuzzy control method is far more better than the traditional direct torque control system.

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.

Permanent Magnet Chatter Absorber with Fuzzy Logic Control

2009 ◽  
Vol 147-149 ◽  
pp. 290-295 ◽  
Author(s):  
Bogdan Broel-Plater ◽  
Stefan Domek ◽  
Arkadiusz Parus
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Logic Control ◽  
Control Algorithm ◽  
Permanent Magnets ◽  
Practical Experience ◽  
High Energy ◽  
Logic Control ◽  
Machine Operators

The paper deals with semi-active chatter absorber based on an electrodynamic transducer built around high-energy permanent magnets. Also, a fuzzy logic control system for the absorber control system has been designed. The principal advantage of fuzzy control is the possibility to implement practical experience gained by machine operators in the control algorithm. Hence, the possibility of factoring such quantities, as vibrations experienced by selected points of the machine-tool, and sound emitted by working machine into the analyzed chatter absorber fuzzy control system has been studied in the paper. The control system has been tested by way of simulation with the use of the process and cutting force models.

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