scholarly journals Fuzzy logic for control Peltier module

2018 ◽  
Vol 19 (6) ◽  
pp. 704-707
Author(s):  
Emil Sadowski ◽  
Tomasz Marek ◽  
Roman Pniewski ◽  
Rafał Kowalik
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Control Process ◽  
Controller Synthesis ◽  
Cell Control ◽  
Control Value ◽  
Peltier Module ◽  
Current Value

The article presents the Peltier cell control system devel-oped by the authors. Due to the non-linear dependence of the cell's efficiency on the current, fuzzy logic was used to determine the control value. In the following parts of the article the actual characteristics of the Peltier cells, the method of determining the control current value (fuzzy controller synthesis). The controller of fuzzy logic and its relation to traditional control in a closed system and obtained results have been presented. The FUDGE software from Motorola was used to implement fuzzy logic. The control algorithm presented in the article will be used to develop cell control system that enables optimization of the Peltier cell control process.

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.

Intelligent Control System Design for a Teleoperated Endoscopic Surgical Robot

2015 ◽  
Vol 789-790 ◽  
pp. 693-699
Author(s):  
Alaa Khalifa ◽  
Ahmed Ramadan
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
System Design ◽  
Trajectory Tracking ◽  
Parallel Manipulator ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Control System Design ◽  
Matlab Simulink

This paper concerns with the control system design for a teleoperated endoscopic surgical manipulator system that uses PHANTOM Omni haptic device as the master and a 4-DOF parallel manipulator (2-PUU_2-PUS) as the slave. PID control algorithm was used to achieve the trajectory tracking, but the error in each actuated joint reached 0.6 mm which is not satisfactory in surgical application. The design of a control algorithm for achieving high trajectory tracking is needed. Simulation on the virtual prototype of the 4-DOF parallel manipulator has been achieved by combining MATLAB/Simulink with ADAMS. Fuzzy logic controller is designed and tested using the interface between ADAMS and MATLAB/Simulink. Signal constraint block adjusted the controller parameters for each actuated prismatic joint to eliminate the overshoot in most of position responses. The simulation results illustrate that the fuzzy logic control algorithm can achieve high trajectory tracking. Also, they show that the fuzzy controller has reduced the error by approximately 50 percent.

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.

scholarly journals FUZZY-КОНТРОЛЕР ПІДТРИМАННЯ МІКРОКЛІМАТУ В ПРИМІЩЕННІ ЗА ЗНАЧЕННЯМИ ІНДЕКСУ ДИСКОМФОРТУ

2018 ◽  
Vol 9 (4) ◽  
Author(s):  
П. В. Новіков ◽  
О. В. Степанець ◽  
Р. П. Саков
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Transfer Functions ◽  
Fuzzy Controller ◽  
Intelligent System ◽  
Rule Base ◽  
Individual Parameter ◽  
Discomfort Index

For microclimate control systems is proposed a control algorithm based on maintaining the desired discomfort index using a fuzzy logic controller. To assess the influence of the environment on humans, it is necessary to determine not only the quantitative value of individual microclimate parameters, but also the result of their overall impact on the human body. The existing complex methods of microclimate control are investigated. An approach to determine the index of discomfort has been analyzed. The values of the discomfort index are divided into ranges, depending on the average comfort sensations in the room for a person. The fundamentals of the theory of fuzzy sets are considered. The fuzzy logic controller is synthesized. A database of rules has been developed based on calculated values of the discomfort index. The intelligent system of automatic maintenance of comfortable microclimate conditions in the room is designed. Based on the calculated values of the discomfort index for all possible variants of the temperature values of dry and wet thermometers, a rule base for the fuzzy controller is built. The computer simulation of the obtained microclimate control system in the room is carried out based on the transfer functions of dry and wet thermometers. The results of mathematical modeling showed the effectiveness of using the proposed control algorithm. The control effect is made after processing the aggregated information directly from two sensors, thereby reducing the number of unnecessary inclusions for small fluctuations of each individual parameter. According to the results of modeling it can be noted compliance with the requirements of the received control system to maintain the desired level of discomfort index in the room, the minimum number of actuator inclusions, no overshoot and energy savings.

scholarly journals An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 51
Author(s):  
Jozef Živčák ◽  
Michal Kelemen ◽  
Ivan Virgala ◽  
Peter Marcinko ◽  
Peter Tuleja ◽  
...  
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Mechanical Design ◽  
Mechanical Ventilator ◽  
Mechanical Ventilators ◽  
Inference System ◽  
Control Approach ◽  
Neuro Fuzzy

COVID-19 was first identified in December 2019 in Wuhan, China. It mainly affects the respiratory system and can lead to the death of the patient. The motivation for this study was the current pandemic situation and general deficiency of emergency mechanical ventilators. The paper presents the development of a mechanical ventilator and its control algorithm. The main feature of the developed mechanical ventilator is AmbuBag compressed by a pneumatic actuator. The control algorithm is based on an adaptive neuro-fuzzy inference system (ANFIS), which integrates both neural networks and fuzzy logic principles. Mechanical design and hardware design are presented in the paper. Subsequently, there is a description of the process of data collecting and training of the fuzzy controller. The paper also presents a simulation model for verification of the designed control approach. The experimental results provide the verification of the designed control system. The novelty of the paper is, on the one hand, an implementation of the ANFIS controller for AmbuBag pressure control, with a description of training process. On other hand, the paper presents a novel design of a mechanical ventilator, with a detailed description of the hardware and control system. The last contribution of the paper lies in the mathematical and experimental description of AmbuBag for ventilation purposes.

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.

Simulation of a New Self-Structured Fuzzy Controller Applied to a Temperature Control Process

2013 ◽  
Vol 4 (3) ◽  
pp. 47-57
Author(s):  
Rafik Lasri ◽  
Ignacio Rojas ◽  
Héctor Pomares ◽  
M. Nemiche
Keyword(s):  
Real Time ◽  
Temperature Control ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Control Process ◽  
The Self ◽  
Fuzzy Controllers ◽  
Current State ◽  
Internal Parameters

A new methodology of Fuzzy Controllers that can change the internal parameters of the controller in real time is presented in this paper. The Self-structured algorithm is able to adapt their rules consequents and re-organize their MFs in real time according to the current state of the controlled plant. Via a simulation of a temperature control process, the authors have proved and demonstrated the effectiveness and usefulness of their control algorithm compared to a conventional FLC under the same condition and using the same Simulated plant.

scholarly journals Online Position Control Performance Improving Applying Incremental Fuzzy Logic Controller

2018 ◽  
Vol 248 ◽  
pp. 02005
Author(s):  
Dirman Hanafi ◽  
Mohamed Najib Ribuan ◽  
Wan HamidahWan Abas ◽  
Hidayat ◽  
Elmy Johana ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Motor Performance ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Peak Time ◽  
Control Performance ◽  
Position Control System

This paper presents the online control system application for improving the DC motor performance. DC motor widely used in industries and many appliances. For this aim fuzzy logic controller is applied. The type of fuzzy controller use is an incremental fuzzy logic controller (IFLC). The IFLC is developed by using MATLAB Simulink Software and implemented in online position control system applying RAPCON board as a platform. The experimental results produced the best gains of the IFLC are 1.785, 0.0056955 and 0.01 for error gain (GE), gain of change error (GCE) and gain of output (GCU) respectively. Its produce smaller rise time, peak time, 0% overshoot and smaller settling time. Beside that the IFLC response also able to follow the set point. The controller response parameters values are also acceptable. It means that the IFLC suitable to be use for improving the position control system performance.

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.

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