Simulation for Temperature Control System of Dyeing Machine Based on Fuzzy Control

2011 ◽  
Vol 317-319 ◽  
pp. 1688-1692
Author(s):  
Min Ling Zhao ◽  
Guo Ping Li ◽  
Xiong Bo Ze ◽  
Cheng Kai Ji
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Decisive Role ◽  
Temperature Control System ◽  
Logic Control

In the process of dyeing, the temperature control of dyeing machine plays a decisive role on the stand or fall quality of fabric. The establishment of the traditional PID controller’s parameters needs a lot of test, which brings many inconvenience.Therefore, it is proposed to control dyeing machine temperature by fuzzy controller. Based on the principle of fuzzy logic control, the model of the temperature control system of dyeing machine is built. At the same time, through the fuzzy logic toolbox in matlab software, fuzzy controller of temperature is designed. Then a comparative simulation of the temperature control system of dyeing machine with matlab has been accomplished. Through the analysis of the results, it is concluded that the temperature system can achieve the higher steady precision.

Research on Fuzzy Control System for Air-Condition in Bus

2012 ◽  
Vol 457-458 ◽  
pp. 998-1001
Author(s):  
Qiu Hua Miao ◽  
Pei Gang Jiao ◽  
Jie Liang
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Logic Control ◽  
Temperature Signal ◽  
Working Principle ◽  
Fuzzy Logic Technique ◽  
Deflection Rate

In this paper fuzzy logic control is introduced in auto adjust control system of air in bus. Fuzzy controller employs fuzzy control model of two inputs and one output. The paper also introduces the hardware framework, working principle and software of the system, analyzing merits of fuzzy logic technique, putting emphasis on the design of the fuzzy controller. In the controlling process, fuzzy controller samples temperature signal in bus and calculate deflection and deflection rate of temperature, looks up corresponding output in controlling table, and calculates its precision, then fuzzy controller gives related signal to motors and valve, acquiring satisfactory effect.

Design Fuzzy Logic Control System of Automatic Irrigation Based on MINI2440 and C8051F410 MCU

2013 ◽  
Vol 739 ◽  
pp. 499-504
Author(s):  
He Xi Zhang ◽  
Dao Cai Chi ◽  
Li Xuan Wang ◽  
Tao Tao Chen ◽  
Yong Tao Wang
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Robust Control ◽  
Fuzzy Control ◽  
Fuzzy Logic Control ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Control Mode ◽  
Logic Control ◽  
Controlling System

In this paper, the fuzzy controlling system of automatic irrigation was prepared and designed based on MINI2440 and C8051F410 MCU, in which MATLAB was embedded in C8051F410 MCU while WINCE5.0 was embedded in MINI2440. In the progress, the WINCE5.0 was developed by using C#. All the simulate results of fuzzy controller were shown by SIMLINK in the system. In this paper, we proposed a novel control mode and gave the Robust Control Algorithm of the fuzzy Control System.

The Application Study of Temperature Control Strategy for Boiler

2013 ◽  
Vol 313-314 ◽  
pp. 462-465
Author(s):  
Guo Qiang Hou ◽  
Ping Lv
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
Steam Temperature ◽  
Application Study ◽  
Fuzzy Control System ◽  
Logic Control

The series fuzzy control system is designed for boiler steam temperature based on the characteristics of boiler steam temperature control. The composition, the principles and the algorithm were presented in this paper. The corresponding fuzzy logic control system is simulated and analyzed with MATLAB.

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.

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.

Research of Temperature Control System Based on Fuzzy Control Algorithm for Mixer

2009 ◽  
Vol 87-88 ◽  
pp. 288-292 ◽  
Author(s):  
Chuan Sheng Wang ◽  
Fu Hai Zhou
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Cooling Water ◽  
Host Computer ◽  
Temperature Control System ◽  
Control Value ◽  
Fuzzy Control Algorithm

The changes of temperature in the rubber mixing process is of great significance. How to ensure the changes of temperature in rubber mixing is an important issue. The article introduces the temperature control system based on the fuzzy control algorithm. Using the host computer as the fuzzy controller, and the host computer educes the control value based on the difference between the reference input and the measure value. The system automatically discharges of high temperature water and automatically adds the appropriate amount of cooling water. The system can ensure the stability of the mixing temperature and ensure the quality of rubber mixing.

PID Parameter Setting Based on Fuzzy Control Algorithm and its Application in the Temperature Control System of Airplane

2012 ◽  
Vol 588-589 ◽  
pp. 1503-1506
Author(s):  
Fang Ding ◽  
Tao Ma
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Control Algorithm ◽  
Control Method ◽  
Fuzzy Controller ◽  
Temperature Control System ◽  
System Control ◽  
Control Effect ◽  
Fuzzy Control Algorithm

This Temperature control system of aircraft cabin is a complex system with nonlinear, time-varying, model inaccurate and work environment uncertain. According to the system control requirements, the fuzzy controller with the characteristic of fast response speed, good stability and strong resistance to interference is used in the study. The system error is adjusted constantly by using fuzzy control algorithm and simulation study is conducted in the software Matlab. The results are showed that control effect of control method used in this study is better than the traditional PID control method, and dynamic performance, steady state accuracy and robustness of system is effectively improved.

Temperature Control System Based on Electronic Boiler

2013 ◽  
Vol 325-326 ◽  
pp. 1197-1201
Author(s):  
Guo Sheng Xu
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Fuzzy Controller ◽  
System Simulation ◽  
Temperature Control System ◽  
Control Effect ◽  
Simulation Research ◽  
Control Regulation ◽  
Control Scheme

Research has been done aimed at the boiler's temperature control system, and available control scheme is put forward. Combining with the output response of control system, simulation research and the control regulation of fuzzy controller are done to analyse, after experiments for many times repeatedly, fuzzy control regulation is ensured. The simulation result indicates that control effect is ideal, which means this scheme is identified as ideal temperature control system scheme.

Control of a Fluidized Bed Combustor Using Fuzzy Logic

1996 ◽  
Vol 118 (1) ◽  
pp. 204-209 ◽  
Author(s):  
S. J. Koffman ◽  
R. C. Brown ◽  
R. R. Fullmer
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Fluidized Bed ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Experimental Results ◽  
Pi Control ◽  
Logic Control ◽  
And Performance ◽  
Fluidized Bed Combustor

Application of fuzzy logic control to a fluidized bed combustor (FBC) is examined. Major aspects of fuzzy control are reviewed, and design of a fuzzy controller for the FBC is described. Selected experimental results are presented, and performance of the fuzzy controller is evaluated through comparisons to results from classical PI control of the combustor.

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