scholarly journals Design of microcontroller-based decentralized controller board to drive chiller systems using PID and fuzzy logic algorithms

2019 ◽  
Vol 234 (1) ◽  
pp. 98-107 ◽  
Author(s):  
Yalcin Isler ◽  
Savas Sahin ◽  
Orhan Ekren ◽  
Cuneyt Guzelis
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Low Cost ◽  
Variable Speed ◽  
Proportional Integral Derivative ◽  
Scroll Compressor ◽  
Proportional Integral ◽  
Output Controller ◽  
Expansion Valve ◽  
Controller Board

This study deals with designing a decentralized multi-input multi-output controller board based on a low-cost microcontroller, which drives both parts of variable-speed scroll compressor and electronic-type expansion valve simultaneously in a chiller system. This study aims to show the applicability of commercial low-cost microcontroller to increase the efficiency of the chiller system, having variable-speed scroll compressor and electronic-type expansion valve with a new electronic card. Moreover, the refrigerant system proposed in this study provides the compactness, mobility, and flexibility, and also a decrease in the controller unit’s budget. The study was tested on a chiller system that consists of an air-cooled condenser, a variable-speed scroll compressor, and a stepper driven electronic-type expansion valve. The R134a was used as a refrigerant fluid and its flow was controlled by electronic-type expansion valve in this setup. Both variable-speed scroll compressor and electronic-type expansion valve were driven by the proposed hardware using either proportional integral derivative or fuzzy logic controller, which defines four distinct controller modes. The experimental results show that fuzzy logic controlled electronic-type expansion valve and proportional integral derivative controlled variable-speed scroll compressor mode give more robustness by considering the response time.

A new control method based on fuzzy controller, time delay estimation, deep learning, and non-dominated sorting genetic algorithm-III for powertrain mount system

2019 ◽  
Vol 26 (13-14) ◽  
pp. 1187-1198 ◽  
Author(s):  
Li-Xin Guo ◽  
Dinh-Nam Dao
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Deep Learning ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral

This article presents a new control method based on fuzzy controller, time delay estimation, deep learning, and non-dominated sorting genetic algorithm-III for the nonlinear active mount systems. The proposed method, intelligent adapter fractions proportional–integral–derivative controller, is a smart combination of the time delay estimation control and intelligent fractions proportional–integral–derivative with adaptive control parameters following the speed range of engine rotation via the deep neural network with the optimal non-dominated sorting genetic algorithm-III deep learning algorithm. Besides, we proposed optimal fuzzy logic controller with optimal parameters via particle swarm optimization algorithm to control reciprocal compensation to eliminate errors for intelligent adapter fractions proportional–integral–derivative controller. The control objective is to deal with the classical conflict between minimizing engine vibration impacts on the chassis to increase the ride comfort and keeping the dynamic wheel load small to ensure the ride safety. The results of this control method are compared with that of traditional proportional–integral–derivative controller systems, optimal proportional–integral–derivative controller parameter adjustment using genetic algorithms, linear–quadratic regulator control algorithms, and passive drive system mounts. The results are tested in both time and frequency domains to verify the success of the proposed optimal fuzzy logic controller–intelligent adapter fractions proportional–integral–derivative control system. The results show that the proposed optimal fuzzy logic controller–intelligent adapter fractions proportional–integral–derivative control system of the active engine mount system gives very good results in comfort and softness when riding compared with other controllers.

scholarly journals PENGONTROL LOGIKA FUZZY UNTUK MENGENDALIKAN KECEPATAN ROTOR MOTOR ARUS SEARAH

Saintek ITM ◽  
2019 ◽  
Vol 32 (1) ◽  
Author(s):  
Sarvaesshwaran Krishna Kumar
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Proportional Integral Derivative ◽  
Proportional Integral

Fuzzy Logic Controller (FLC) telah banyak digunakan dalam aplikasi untuk mengontrol kecepatan motor arus searah. Kinerja dengan kemampuan untuk mengontrol secara otomatis diperlukan. Dalam proyek ini, kinerja motor arus searah yang dipilih telah dikontrol menggunakan pengontrol Proportional Integral Derivative (PID) dan FLC telah dipelajari. Untuk tujuan itu, nilai maksimum kecepatan swap untuk mencapai nilai kecepatan yang telah ditentukan dan juga waktu yang dibutuhkan untuk mencapai nilai kecepatan target yang stabil telah diidentifikasi dan dianalisis untuk memverifikasi perilaku pengontrol PID serta FLC. Oleh karena itu, penyesuaian harus dilakukan pada FLC untuk memastikan bahwa kinerja yang dihasilkan sesuai dengan yang diinginkan... Kontrol kecepatan motor arus searah yang dilakukan oleh pengontrol PID dan pengontrol FLC adalah dengan menggunakan perangkat lunak MATLAB. Hasil menunjukkan bahwa menggunakan FLC, kecepatan maksimum dari kemungkinan adalah minimal, gelombang transien minimum dan juga nilai kesalahan dalam kondisi kecepatan stabil minimum telah dicapai dibandingkan dengan menggunakan pengontrol Controlled Integral Derivative (PID) konvensional.

scholarly journals Comparison between proportional, integral, derivative controller and fuzzy logic approaches on controlling quarter car suspension system

2018 ◽  
Vol 184 ◽  
pp. 02018
Author(s):  
Ahmet Mehmet Karadeniz ◽  
Alsabbagh Ammar ◽  
Husi Dr.Geza
Keyword(s):  
Fuzzy Logic ◽  
Public Transportation ◽  
Fuzzy Logic Controller ◽  
Suspension System ◽  
Maximum Efficiency ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Car Suspension ◽  
Quarter Car

Developing and constantly changing technologies, efforts to achieve maximum efficiency with minimum fuel consumption, as well as the development of comfort and safety systems, have become very essential topic in car manufacturing and design. Whereas comfort and security were not given a high importance in the first produced cars, they are indispensable elements of today's automobiles. Since public transportation uses road in large scale, the need for safety and repose is also increasing. Nowadays, vehicles have better security and comfort systems, which react very quickly to all kinds of loads and different cases of driving (braking, acceleration, high speed, cornering), where the tires can keep the road at its best, utilizing an advanced suspension system. In this study, a quarter-car model was fulfilled using LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) software. The control of this model has been realized by applying two different controllers. PID (proportional, integral, derivative) controller which is a common and conventional control method and the Fuzzy Logic controller which is considered as an expert system that is becoming more and more widely used. In both control approaches, controlling the suspension system was achieved successfully. However; It has been determined that controlling the system using Fuzzy Logic controller gave better dynamic response than applying the PID controller for the quarter car suspension model that has been used in the direction of this study.

Development of Proportional–Integral–Derivative and Fuzzy Control Strategies for Navigation in Agricultural Environments

2017 ◽  
Vol 140 (6) ◽  
Author(s):  
Stephanie Bonadies ◽  
Neal Smith ◽  
Nathan Niewoehner ◽  
Andrew S. Lee ◽  
Alan M. Lefcourt ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Food Quality ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Control Strategies ◽  
Working Hours ◽  
Quality And Safety ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Food Quality And Safety

Farming and agriculture is an area that may benefit from improved use of automation in order to increase working hours and improve food quality and safety. In this paper, a commercial robot was purchased and modified, and crop row navigational software was developed to allow the ground-based robot to autonomously navigate a crop row setting. A proportional–integral–derivative (PID) controller and a fuzzy logic controller were developed to compare the efficacy of each controller based on which controller navigated the crop row more reliably. Results of the testing indicate that both controllers perform well, with some differences depending on the scenario.

scholarly journals Design and simulation of a normalized fuzzy logic controller for the quadruple-tank process

2020 ◽  
Vol 18 (1) ◽  
pp. 227
Author(s):  
Wameedh Riyadh Abdul-Adheem
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Industrial Processes ◽  
Stable Operation ◽  
Design Tools ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Control Techniques ◽  
Classical Control

<p class="MsoNormal" style="margin-top: 6.0pt; text-align: justify;">Industrial processes include multivariable systems and nonlinearities. These conditions must be effectively controlled to ensure a stable operation. A proportional–integral–derivative controller and other classical control techniques provide simple design tools to designers, but cannot accommodate nonlinearities in industrial processes. In this study, the quadruple-tank process, which is one of the most widely used processes in the chemical industry, was selected as the research object.  To examine this process, a fuzzy logic controller, instead of an exact mathematical model, was proposed to ensure the reliability of the experience. A modification was proposed to facilitate the design process. To check the validity of the proposed controller, it was compared with the conventional proportional–integral controller. The former exhibited acceptable performance.</p><table class="MsoTableGrid" style="width: 444.85pt; border-collapse: collapse; border: none; mso-border-alt: solid windowtext .5pt; mso-yfti-tbllook: 1184; mso-padding-alt: 0cm 5.4pt 0cm 5.4pt;" width="0" border="1" cellspacing="0" cellpadding="0"><tbody><tr style="mso-yfti-irow: 0; mso-yfti-firstrow: yes; mso-yfti-lastrow: yes; height: 63.4pt;"><td style="width: 290.6pt; border: none; border-top: solid windowtext 1.0pt; mso-border-top-alt: solid windowtext .5pt; padding: 0cm 5.4pt 0cm 5.4pt; height: 63.4pt;" valign="top" width="593"><p class="MsoNormal" style="margin-top: 6.0pt; text-align: justify;"><span style="mso-ascii-font-family: 'Times New Roman'; mso-ascii-theme-font: major-bidi; mso-hansi-font-family: 'Times New Roman'; mso-hansi-theme-font: major-bidi; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi;">Industrial processes include multivariable systems and nonlinearities. These conditions <span style="mso-no-proof: yes;">must be effectively</span> controlled to ensure a stable operation. A proportional–integral–derivative controller and other classical control techniques provide <span style="mso-no-proof: yes;">simple</span> design tools to designers, <span style="mso-no-proof: yes;">but</span> cannot accommodate nonlinearities in industrial processes. In this study, the quadruple</span><span style="mso-ascii-font-family: 'Times New Roman'; mso-ascii-theme-font: major-bidi; mso-hansi-font-family: 'Times New Roman'; mso-hansi-theme-font: major-bidi; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi; mso-bidi-language: AR-IQ;">-tank process</span><span style="mso-ascii-font-family: 'Times New Roman'; mso-ascii-theme-font: major-bidi; mso-hansi-font-family: 'Times New Roman'; mso-hansi-theme-font: major-bidi; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi;">, which is one of the most widely used processes in the chemical industry, was selected as the research object.<span style="mso-spacerun: yes;">  </span>To examine this process, a</span><span style="mso-ascii-font-family: 'Times New Roman'; mso-ascii-theme-font: major-bidi; mso-hansi-font-family: 'Times New Roman'; mso-hansi-theme-font: major-bidi; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi; mso-bidi-language: AR-IQ;"> fuzzy logic controller, instead of an </span><span style="mso-ascii-font-family: 'Times New Roman'; mso-ascii-theme-font: major-bidi; mso-hansi-font-family: 'Times New Roman'; mso-hansi-theme-font: major-bidi; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi;">exact mathematical model,</span><span style="mso-ascii-font-family: 'Times New Roman'; mso-ascii-theme-font: major-bidi; mso-hansi-font-family: 'Times New Roman'; mso-hansi-theme-font: major-bidi; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi;">was<span style="mso-no-proof: yes;"> proposed</span> to ensure the reliability of the experience. </span><span style="mso-ascii-font-family: 'Times New Roman'; mso-ascii-theme-font: major-bidi; mso-hansi-font-family: 'Times New Roman'; mso-hansi-theme-font: major-bidi; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi; mso-bidi-language: AR-IQ;">A modification was proposed to facilitate the design process. To check the <span style="mso-no-proof: yes;">validity</span> of the proposed controller, it was compared with the conventional proportional</span><span style="mso-ascii-font-family: 'Times New Roman'; mso-ascii-theme-font: major-bidi; mso-hansi-font-family: 'Times New Roman'; mso-hansi-theme-font: major-bidi; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi;">–</span><span style="mso-ascii-font-family: 'Times New Roman'; mso-ascii-theme-font: major-bidi; mso-hansi-font-family: 'Times New Roman'; mso-hansi-theme-font: major-bidi; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi; mso-bidi-language: AR-IQ;">integral <span style="mso-no-proof: yes;">controller. The former exhibited</span> <span style="mso-no-proof: yes;">acceptable</span> performance.</span></p><p class="MsoNormal" style="margin-top: 6.0pt; text-align: justify;"> </p></td></tr></tbody></table>

Design and Implementation of a Fuzzy Logic Controller for Two Wheeled Self Balancing Robot

2011 ◽  
Vol 403-408 ◽  
pp. 4918-4925
Author(s):  
Umar Farooq ◽  
Muhammad Usman Asad ◽  
Athar Hanif ◽  
K.M. Hasan ◽  
Muhammad Amar
Keyword(s):  
Fuzzy Logic ◽  
Tilt Angle ◽  
Fuzzy Logic Controller ◽  
Low Cost ◽  
Single Input Single Output ◽  
Output Controller ◽  
Design And Implementation ◽  
Single Output ◽  
Single Input ◽  
Balancing Robot

This paper describes the design of a simple fuzzy logic controller for self balancing robot. The proposed controller is single input, single output controller. The input to the controller is tilt angle and the output forms the speed commands for the motors. The controller is designed using MATLAB and implemented with a low cost readily available AT89C52 microcontroller. Results have proved the validity of the proposed controller for balancing the robot.

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