CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Fuzzy PID Control for Networked Control System of DC Motor with Random Design

by Kota Bala Murali Krishna, B.v.s. Goud
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 52 - Number 7
Year of Publication: 2012
Authors: Kota Bala Murali Krishna, B.v.s. Goud
10.5120/8215-1635

Kota Bala Murali Krishna, B.v.s. Goud . Fuzzy PID Control for Networked Control System of DC Motor with Random Design. International Journal of Computer Applications. 52, 7 ( August 2012), 24-28. DOI=10.5120/8215-1635

@article{ 10.5120/8215-1635,
author = { Kota Bala Murali Krishna, B.v.s. Goud },
title = { Fuzzy PID Control for Networked Control System of DC Motor with Random Design },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 52 },
number = { 7 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 24-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume52/number7/8215-1635/ },
doi = { 10.5120/8215-1635 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:51:40.278376+05:30
%A Kota Bala Murali Krishna
%A B.v.s. Goud
%T Fuzzy PID Control for Networked Control System of DC Motor with Random Design
%J International Journal of Computer Applications
%@ 0975-8887
%V 52
%N 7
%P 24-28
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Separately excited DC motor speed can be controlled using PID controller and fuzzy logic controller. The proportional, integral and derivate (KP, KI, KD) gains of the PID controller are adjusted according to FUZZY LOGIC. First, the fuzzy logic controller is designed according to fuzzy rules so that the systems are fundamentally robust. There are 25 fuzzy rules for self-tuning of each parameter of PID controller. The FLC has two inputs. One is the motor speed error between the reference and actual speed and the second is change in speed error (speed error derivative). Secondly, the output of the FLC i. e. the parameters of PID controller are used to control the speed of the separately excited DC Motor. The study shows that both precise characters of PID controllers and flexible characters of fuzzy controller are present in fuzzy self-tuning PID controller. The fuzzy self-tuning approach implemented on a conventional PID structure was able to improve the dynamic as well as the static response of the system. Comparison between the conventional output and the fuzzy self-tuning output was done on the basis of the simulation result obtained by MATLAB. The simulation results demonstrate that the designed self-tuned PID controller realize a good dynamic behavior of the DC motor, a perfect speed tracking with less rise and settling time, minimum overshoot, minimum steady state error and give better performance compared to conventional PID controller.

References
  1. B. J. Chalmers, "Influence of saturation in brushless permanent magnet drives. " IEE proc. B, Electr. Power Appl, vol. 139, no. 1, 1992.
  2. C. T. Johnson and R. D. Lorenz, "Experimental identification of friction and its compensation in precise, position controlled mechanism. " IEEE Trans. Ind ,Applicat, vol. 28, no. 6, 1992.
  3. Zhang, N. Wang and S. Wang, "A developed method of tuning PID controllers with fuzzy rules for integrating process," Proceedings of the American Control Conference,Boston, 2004, pp. 1109-1114.
  4. K. H. Ang, G. Chong and Y. Li, "PID control system analysis, design and technology," IEEE transaction on Control System Technology, Vol. 13, No. 4, 2005, pp. 559-576.
  5. H. X. Li and S. K. Tso, "Quantitative design and analysis of Fuzzy Proportional-Integral-Derivative Control- a Step towards Auto tuning", International journal of system science, Vol. 31, No. 5, 2000, pp. 545-553.
  6. Thana Pattaradej, Guanrong Chen and PitikhateSooraksa, "Design and Implementation of Fuzzy PID Control of a bicycle robot", Integrated computer-aided engineering, Vol. 9, No. 4, 2002.
  7. Weiming Tang, Guanrong Chen and Rongde Lu, "A Modified Fuzzy PI Controller for a Flexible-joint Robot Arm with Uncertainties", Fuzzy Set and System, 118 (2001) 109-119.
  8. PavolFedor, Daniela Perduková, "A Simple Fuzzy Controller Structure,"ActaElectrotechnica ET Informatica No. 4, Vol. 5, 2005.
  9. Maher M. F. Algreer andYhyaR. M. Kuraz, "Design Fuzzy Self Tuning of PID Controller for Chopper-Fed DC Motor drive. " Kuraz.
  10. BomedieneAlloua ,AbdellahLaoufBrahimGasbaoui and ABdessalamAbderrahamani, "Neuro-Fuzzy DC Motor speed Control Using Particle Swarm Optimization," Leonaro Electronic Journal of Practices and Technologies ISSN,1583-1078.
  11. ManafeddinNamazov and OnurBasturk, "DC motor position control using fuzzy proportional-derivative controllers with different defuzzification methods," Turkish Journal of Fuzzy Systems (eISSN: 1309–1190), Vol. 1, No. 1, pp. 36-54, 2010.
  12. Wang Xiao-kan, Sun Zhong-liang, Wanglei, Feng Dong-qing, "Design and Research Based on Fuzzy PID-Parameters Self-Tuning Controller with MATLAB," Advanced Computer Theory and Engineering, International Conference on, pp. 996-999, 2008 International Conference on Advanced Computer Theory and Engineering, 2008.
  13. GaddamMallesham and AkulaRajani ,"AUTOMATIC TUNING OF PID CONTROLLER USING FUZZY LOGIC . " 8th International Conference on DEVELOPMENT AND APPLICATION SYSTEMS Suceava, Romania, May 25 – 27, 2006.
  14. M. Chow and A. Menozzi ,"on the comparison of emerging and conventional techniques for DC motor control" proc. IECON ,PP. 1008-1013,1992.
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy PID

Powered by PhDFocusTM