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

A PSO Optimized Fuzzy Control Scheme for Mobile Robot Path Tracking

by Turki Y. Abdalla, Abdulkareem. A. A
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 76 - Number 2
Year of Publication: 2013
Authors: Turki Y. Abdalla, Abdulkareem. A. A
10.5120/13217-0608

Turki Y. Abdalla, Abdulkareem. A. A . A PSO Optimized Fuzzy Control Scheme for Mobile Robot Path Tracking. International Journal of Computer Applications. 76, 2 ( August 2013), 11-17. DOI=10.5120/13217-0608

@article{ 10.5120/13217-0608,
author = { Turki Y. Abdalla, Abdulkareem. A. A },
title = { A PSO Optimized Fuzzy Control Scheme for Mobile Robot Path Tracking },
journal = { International Journal of Computer Applications },
issue_date = { August 2013 },
volume = { 76 },
number = { 2 },
month = { August },
year = { 2013 },
issn = { 0975-8887 },
pages = { 11-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume76/number2/13217-0608/ },
doi = { 10.5120/13217-0608 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:48:47.288420+05:30
%A Turki Y. Abdalla
%A Abdulkareem. A. A
%T A PSO Optimized Fuzzy Control Scheme for Mobile Robot Path Tracking
%J International Journal of Computer Applications
%@ 0975-8887
%V 76
%N 2
%P 11-17
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a fuzzy controllers type Takagi_Sugeno is optimized by method of Particle Swarm Optimization (PSO). This algorithm automatically adjust the membership function of fuzzy controllers to control a trajectory of nonholonomic mobile robot that involves path trajectory using two optimized fuzzy controllers one for speed control and the other for azimuth control. The mobile robot is modelled in Simulink and PSO algorithm is implemented using MATLAB. Simulation results show good performance for the proposed control scheme. The results will compared with PSO-PID controllers that control the same model of mobile robot.

References
  1. Y. Shinoda, Y. Tan, J. Nakata and R. Beuran. 2007. Collaborative Motion Planning of Autonomous Robots. School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa Japan.
  2. R. A. Felder. 1998. Mobile Robot Simulation of Clinical Laboratory Deliveries. M. Sc. Thesis, the University of Virginia, U. S. A.
  3. Kennedy J, Eberhart RC. 1995 Particle swarm optimization. In Proc. IEEE International Conference on Neural Networks, WA Australia, p. 1942–8
  4. Kennedy J, Eberhart RC, Shi Y, Swarm Intelligence, Morgan Kaufmann Publishers, 2001
  5. Eberhart RC, Shi Y. 2001. Particle Swarm Optimization: developments, applications and resources. In Proc. Congress on evolutionary computation, Seoul, Korea, p. 81–6.
  6. A. Haj-Ali and H. Ying. 2004. Structural Analysis of Fuzzy Controllers with Nonlinear Input Fuzzy Sets in Relation to Nonlinear PID Control with Variable Gains. Associate Editor Gary G. Yen under the direction of Editor Robert R. Bitmead, Wayne State University , Detroit , MI48202 ,USA .
  7. D. R. Shircliff. 2002 Build A Remote-Controlled Robot. eBook, Copyright © by The McGraw-Hill Companies.
  8. G. Mester. 2007 Obstacle Avoidance of Mobile Robots in Unknown Environments. SISY, International Symposium on Intelligent Systems and Informatics 24-25 Subotica, Serbia.
  9. A. Albagul and Wahyudi. 2004. Dynamic Modelling and Adaptive Traction Control for Mobile Robots. 30th Annual Conference of the IEEE Industrial Electronics Society, November 2 - 6, Susan, Korea.
  10. M. A. Abido. 2002 Optimal design of power-system stabilizers using particleswarm optimization. IEEE Trans. Energy Conversion, vol. 17, pp. 406-413.
  11. E. N. moret. 2003. Dynamic Modeling And Control Of a Car-like Robot. Master's thises, Virginia Polytechnic Institute and state University.
  12. P. Kachoor and M. tomizuka. 1995. Vvehicle Ccontrol For Automated Hhighway Systems For Improve Lateral Maneuverability. in IEEE International conference on systems,Man, and Cybernetics , Vancouver ,B. C. , Canada , vol. 1,pp. 777-782.
  13. Duc Do,K. ,Zhong-Ping j. ,Pan,J. 2004. A Global Output-feedback Controller For Simultaneous Tracking And Stabilization of Unicycle-Type Mmobile Robots. IEEE Trans. Automat Contr. , V30,N3,pp. 589-594.
  14. E J. Kennedy and R. Eberhart. 1994 Particle Swarm Optimization. In Proc. IEEE Int. Conf. Neural Networks , vol. IV, Perth, Australia, 1995,pp. 1942–1948.
  15. Y. Shi, R. Eberhart. 1998. A Modified Particle Swarm Optimizer. Proc. IEEE Int. Conf. on Evolutionary Computation, pp. 69-73.
  16. J S. Tong, H. X. LI and G. Chen. 2003. Adaptive Fuzzy Decentralized Control for a Class of Large-Scale Nonlinear Systems. IEEE Trans. on Cybern. Man Sys. , Part B.
  17. H. Ying. 1998. Constructing Nonlinear Variable Gain Controllers via the Takagi – Sugeno Fuzzy Control. IEEE Transactions on Fuzzy, Syst. ,vol. 6,pp. 226–234.
  18. K. M. Zahrani. 2005. Fuzzy Takagi-Sugeno and LMS Baded Control Techniques. M. Sc thesis, Fahd University of Petroleum and Minerals.
  19. . Hermadi. 2004. Genetic algorathm based test data generator. M. Sc. Thesis, King Fahd university of petroleum & minerals. Dhahran, Saudi Arabia.
  20. K. C. Ng, M. M. Trivedi. 1998. A Neuro – Fuzzy Controller for Mobile Robot Navigation and Multirobot Convoying. IEEE Trans. on Systems, Man and Cybernetics-Part B: Cybernetics, Vol. 28, No. 6, pp. 829-840, ISSN 1083-4419.
  21. K. H. Sedighi, K. Ashenayi, T. W. Manikas, R. L. Wainwright and H. M. Tai. 2003. Autonomous Local Path Planning for a Mobile Robot Using a Genetic Algorithm. Proceedings of the IEEE Conference on Robotics and Automation, Sacramento, California, 7-12, pp. 1398-1404.
  22. S. E. Mahmoudi , A. A. Bitaghsir , B. Forouzandeh and A. R. Marandi. 2004. A New Genetic Method for Mobile Robot Navigation. Electrical and Computer Engineering Dep. University of Tehran, P. O Box : 14395/515, IRAN.
Index Terms

Computer Science
Information Sciences

Keywords

Mobil Robot Fuzzy Control Particle Swarm Optimization Kinematic and Dynamic Model Particle Swarm Fuzzy controller (PSFC) PSO-PID

Powered by PhDFocusTM