Fuzzy Logic and Fuzzy Control

1994 ◽  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control

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.

MPPT Strategy of PV System Based on Adaptive Fuzzy Control

2014 ◽  
Vol 1008-1009 ◽  
pp. 63-67
Author(s):  
Jia Yuan ◽  
Yu Jiang Wang ◽  
Jing Hong Cui ◽  
Hui Li Zheng ◽  
Liu Bin ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Adaptive Fuzzy Control ◽  
Maximum Power ◽  
Solar Pv ◽  
Step Method ◽  
Photoelectric Conversion ◽  
Maximum Power Point ◽  
Adaptive Fuzzy ◽  
Power Point

In order to use photovoltaic cell effectively and improve its photoelectric conversion efficiency, the maximum power point of photovoltaic generation system should be tracked rapidly and stably [1]. Taking into account the solar PV systems are often affected by external factors,it is difficult to determine system parameters, and has a strong non-linear,so this paper,a adaptive fuzzy logic control technology for STP0950S-36 type of independent photovoltaic systems to a adaptive fuzzy controller design method, and using MATLAB/SIMULINK,fuzzy logic toolbox for simulation tools such as maximum power point control,adaptive fuzzy control simulation results of MPPT with fixed step method compared to fixed-step method was found to reach steady there is a certain state after the fluctuation,The results show that the method can quickly and correctly track change of MPP in different light intensity and the system has excellent stability performance.

scholarly journals IoT Heating Solution for Smart Home with Fuzzy Control

2020 ◽  
Vol 26 (6) ◽  
pp. 747-761
Author(s):  
Łukasz Apiecionek ◽  
Jacek Czerniak ◽  
Dawid Ewald ◽  
Mateusz Biedziak
Keyword(s):  
Fuzzy Logic ◽  
Internet Of Things ◽  
Fuzzy Control ◽  
Smart Home ◽  
Control Method ◽  
Computer Systems ◽  
The Internet ◽  
Climate Chamber

There is currently an era of Internet of Things in the computer systems, which consists in connecting all possible devices to the Internet in order to provide them with new functionalities and thus { to improve the user's life standard. One of such solutions could be Smart Home. The possibility of monitoring inner environment is required for such solutions. Such monitoring provides potential for e.g. better heating control. The authors of this paper propose some heating control method with Fuzzy Logic. The proposed method was tested in a special climate chamber. The authors provided conclusions at the end of the paper.

The Application of MATLAB for Fuzzy Control System Simulation

2014 ◽  
Vol 494-495 ◽  
pp. 1306-1309 ◽  
Author(s):  
Xian Qiu Xu
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Control ◽  
System Simulation ◽  
Paper Briefly ◽  
C Language ◽  
Fuzzy Control System ◽  
Function Module

The design of fuzzy control system is one of the important problems of the application of fuzzy control system. And the system simulation is an important step in the design of and the necessary guarantee. This paper briefly introduces the MATLAB language, the fuzzy logic toolbox, and SILMULINK toolbox. Then the examples, this method overcome the traditional in c language simulation of complex and inconvenient shortcoming. It is easy to fuzzy control system simulation, direct and fast. Finally also introduced several methods of create SILMULINK user s function module.

Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems

2001 ◽  
Vol 54 (6) ◽  
pp. B102-B103 ◽  
Author(s):  
Guanrong Chen, ◽  
Trung Tat Pham, ◽  
NM Boustany,
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Fuzzy Sets ◽  
Control Systems

Design and Implementation of an Intelligent Cleaning Robot Based on Fuzzy Control

2014 ◽  
Vol 1003 ◽  
pp. 221-225
Author(s):  
Hai Yan Liu
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Control Method ◽  
Sensor System ◽  
Service Robots ◽  
Design And Implementation ◽  
Cleaning Robot ◽  
New Development ◽  
Development Area

Nowadays, intelligent cleaning robot is widely used in housecleaning, hotel and office for cleaning in a half--automatic way or full--automatic way. In recent years, the development of cleaning robot has brought increasing attention in overseas and domestic, and it has become a new development area in the field of service robots. This paper designs an intelligent cleaning robot, which could realize move freely under the control of obstacle avoidance strategies based on the fuzzy logic. According to the information of obstacles from the sensor system, the obstacle avoidance system is built by the fuzzy control method to make the cleaning robot avoid the obstacles autonomously.

Control of Automobile's Automatic Parking

2011 ◽  
Vol 339 ◽  
pp. 28-31
Author(s):  
Hong Mei
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Steering Wheel ◽  
Experienced Driver ◽  
Parking System ◽  
Automatic Parking ◽  
Conventional Methods ◽  
The Ideal

An automatic parking controller is proposed. Fuzzy control is taken to simulate the action of experienced driver as an alternative to conventional methods. The angle between the midline of the car and ideal path and the distance between the midpoint of the car and the ideal path are taken as the inputs of the fuzzy controller. The angle of the steering wheel is taken as the output of the fuzzy controller. A set of fuzzy logic rules are build for reasoning. With sensors installed in the car to replace people’s eyes and computer to replace people’s brain, the automatic parking system is more precise and quicker than human’s parking. At last, simulation is made and proved the validity of the proposed method.

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