We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

An Adaptive Fuzzy Logic Controller Trained by Particle Swarm Optimization for Line of Sight Stabilization

by Shahida Khatoon, Ravinder Singh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 39 - Number 4
Year of Publication: 2012
Authors: Shahida Khatoon, Ravinder Singh
10.5120/4810-7004

Shahida Khatoon, Ravinder Singh . An Adaptive Fuzzy Logic Controller Trained by Particle Swarm Optimization for Line of Sight Stabilization. International Journal of Computer Applications. 39, 4 ( February 2012), 32-36. DOI=10.5120/4810-7004

@article{ 10.5120/4810-7004,
author = { Shahida Khatoon, Ravinder Singh },
title = { An Adaptive Fuzzy Logic Controller Trained by Particle Swarm Optimization for Line of Sight Stabilization },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 39 },
number = { 4 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 32-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume39/number4/4810-7004/ },
doi = { 10.5120/4810-7004 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:25:35.116242+05:30
%A Shahida Khatoon
%A Ravinder Singh
%T An Adaptive Fuzzy Logic Controller Trained by Particle Swarm Optimization for Line of Sight Stabilization
%J International Journal of Computer Applications
%@ 0975-8887
%V 39
%N 4
%P 32-36
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The design, operation and control of stabilization -tracking systems has been a challenging task for the scientists and engineers with the present day requirements of modern aged sophistication of these systems. The conventional control concepts have been outplayed by the optimal control techniques with the evolution of the modern control theory. Moreover, due to the problems associated with modern control techniques have motivated the engineers to apply intelligent technique to circumvent these difficulties. An attempt has been made to design and feasibility of an adaptive Particle Swarm Optimization (PSO) based fuzzy logic controller for stabilization-tracking system. The simulation results obtained in the study demonstrate the feasibility of the designed controllers.

References
  1. C.C Lee, “ Fuzzy logic in control systems: Fuzzy logic controller – part 1,. IEEE Trans. Syst. Man Cybern. 20(2),404-418 (1990)
  2. C.C Lee, “ Fuzzy logic in control systems: Fuzzy logic controller – part 2,. IEEE Trans. Syst. Man Cybern. 20(2),419-435 (1990) Charles Elkan - The Paradoxical Success of Fuzzy Logic.
  3. M. Hellmann- Fuzzy Logic Introduction.
  4. Chun-Yi Su and Yury Stepanenko - Adaptive Control of a Class of Nonlinear Systems with Fuzzy Logic.
  5. Lotfi A. Zadeh - Is There a Need for Fuzzy Logic.
  6. Jiasheng Zhang, Dingwen Yu and Shiqing Qi Structural research of fuzzy PID controllers.
  7. J. A. R. Krishna Moorty, Rajeev Maratheand Hari Babu - Fuzzy controller for line-of-sight stabilization systems.
  8. Constantin von Altrock - Recent Successful Fuzzy Logic Applications in Industrial Automation.
  9. Cihan Karakuzu- Fuzzy controller training using particle swarm optimization for nonlinear system control,ISA Trans. 47, 229-239(2008)
  10. Jang JS, self-learning fuzzy controllers based on temporal back propogation, IEEE Trans. Neural Network 1992;3(5):723-41
  11. Reeves CR. Modern heuristic techniques for combinational problems. New York:Wley:1993.
  12. Lin CT,Lee CSG, Supervised and unsupervised learning with fuzzy similarity for neural network-based fuzzy logic control systems, In:Fuzzy sets,neural network, and soft computing . New York: Van Nostrand Reinhold; 1994, 85-125
  13. Chen J, Rine D. Training fuzzy logic based software components by combining adaptation algorithms.Int J Softw Comput 1998;2(2):48-60
  14. Lin CT, Lee CSG. Neural fuzzy systems: a neuro-fuzzy synergism to intelligent system. Englewood Cliffs (NJ):Prentice Hall;1996.
  15. Parrott Daniel, Li Xiadong. Locating and tracking multiple dynamic optima by a particle swarm model using speciation . IEEE Trans. Evol Comput 2006;10(4):440-58.
  16. Clerc M, Kennedy J. The particle swarm-explosion, stability, and convergence in multidimensional complex space. IEEE Trans Evol Comput 2002;6(1):58-73
  17. Jang J-SR.ANFIS; adaptive networkbased fuzzy inference system. IEEE trans Syst Man Cybern 1993;23(3):665-85.
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy logic controller Line of sight stabilization adaptive particle swarm optimization

Powered by PhDFocusTM