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Adaptive Fuzzy FOPID Control Scheme for Path tracking of Mobile Robot

by Turki Y. Abdalla
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 22
Year of Publication: 2018
Authors: Turki Y. Abdalla
10.5120/ijca2018917887

Turki Y. Abdalla . Adaptive Fuzzy FOPID Control Scheme for Path tracking of Mobile Robot. International Journal of Computer Applications. 181, 22 ( Oct 2018), 1-5. DOI=10.5120/ijca2018917887

@article{ 10.5120/ijca2018917887,
author = { Turki Y. Abdalla },
title = { Adaptive Fuzzy FOPID Control Scheme for Path tracking of Mobile Robot },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2018 },
volume = { 181 },
number = { 22 },
month = { Oct },
year = { 2018 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number22/30014-2018917887/ },
doi = { 10.5120/ijca2018917887 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:09:54.397541+05:30
%A Turki Y. Abdalla
%T Adaptive Fuzzy FOPID Control Scheme for Path tracking of Mobile Robot
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 22
%P 1-5
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper present a new control method for path tracking of mobile robot based on using fuzzy logic and FOPID controller . Two FOPID controllers are used. Parameters of the two FOPID controllers are optimized offline using genetic algorithm.. These optimized FOPID controllers are used for speed control and azimuth control. Parameters of these controller are adjusted online via fuzzy system. Each FOPID controller is supported by a fuzzy controller for adjusting the parameters online. The adjusting mechanism in the designed control scheme work well when there are variations in the plant parameters and changes in operating conditions.

References
  1. G. Mester, "Intelligent Mobile Robot Motion Control in Unstructured Environments," Acta Polytechnica Hungarica ,Vol.07, No.04, 2010.
  2. Y. Wang, S. Wang, R. Tan and Y. Jiang,"Motion control of a wheeled mobile robot using digital acceleration control method", International Journal of Innovative Computing, Information and Control, Vol.09, No.01, pp.387-396, 2013.
  3. H. Ouarda, "Novel Mobile Robot Path planning Algorithm", International Journal of system applications, engineering and development, Vol.04, No.04, 2010.
  4. T. Lee, K. Song ,C. Lee and C. Teng, “Tracking Control of Mobile Robots Using Saturation Feedback Controller”, IEEE Transactions on control system technology , Vol.09, No.2, Taiwan, March 2001.
  5. P. Lahoty and G. Parmar, "A Comparative Study of Tuning of PID Controller using Evolutionary Algorithms", International Journal of Emerging Technology and Advanced Engineering, Vol.03, No.01, 2013.
  6. M. I. Hamzah , Turki Y Abdalla, “ Mobile Robot Navigation using Fuzzy Logic and Wavelet Network” , International Journal of Robotics and Automation, Vol. 3, Nol. 3, 2014.
  7. Turki Y Abdalla, AA Abdulkareem, " A PSO Optimized Fuzzy Control Scheme for Mobile Robot Path Tracking", International Journal of Computer applications, Vol. 76, No. 2, 2013.
  8. Turki Y Abdalla, " Fuzzy Fine tuning of an Optimized PID Control Scheme for Mobile Robot Trajectory Tracking, International Journal of Computer applications, Vol. 181, No. 19, 2018.
  9. V. Kumar, K. P. S. Rana, J. Kumar, P. Mishra, and S. S Nair, "A Robust Fractional Order Fuzzy P + Fuzzy I + Fuzzy D Controller for Nonlinear and Uncertain System", Springer International Journal of Automation and Computing, pp. 474-488, (2017).
  10. R. M. Asl, E. Pourabdollah, and M. Salmani, "Optimal fractional order PID for a robotic manipulator using colliding bodies design Soft Comput, Springer Berlin Heidelberg, (2017). (2017).
  11. Ah. Dumlu, and K. Erenturk, "Trajectory Tracking Control for a 3-DOF Parallel Manipulator Using Fractional Order PI(D( Control", IEEE Transactions on Industrial Electronics, Vol.61, No.7, (2013).
  12. M. A. Abido, “Optimal design of power-system stabilizers using particle swarm optimization,” IEEE Trans. Energy Conversion, vol. 17, pp.406-413, Sep. 2002.
  13. Wissam H. Al-Mutar, Turki Y. Abdalla, "Quarter Car Active Suspension System Control Using PID Controller tuned by PSO", Iraq J. of Electrical and Electronic Engineering, Vol. 11, NO. 2. 2015
  14. D. R. Shircliff, "Build A Remote-Controlled Robot", eBook, Copyright © by The ,McGraw-Hill Companies, 2002.
  15. . ] M. I. Ribeiro and P. Lima, "Kinematics Models of Mobile Robots", Av. Rovisco Pais, 11049-001 Lisboa, April, 2002
  16. G. Mester, "Obstacle Avoidance of Mobile Robots in Unknown Environments", SISY, International Symposium on Intelligent Systems and Informatics 24-25 Subotica, Serbia, August, 2007.
  17. A. Albagul and Wahyudi, "Dynamic Modelling and Adaptive Traction Control for Mobile Robots", 30th Annual Conference of the IEEE Industrial Electronics Society, November 2 - 6, Susan, Korea 2004.
  18. P. J. Fleming and R. C. Purshouse," Genetic algorithms in control systems engineering", Research Report No. 789 S1 3JD, University of Sheffield, May UK, 2001.
  19. A.A. Ahmed, T.Y. Abdalla, AA Abed, “Path planning of mobile robot by using modified optimized potential field method” international journal of computer applications, vol. 113, No.4, 2015.
  20. T.Y. Abdalla, AA Abed, AA Ahmed, “Mobile robot navigation using PSO-optimized fuzzy artificial potential field with fuzzy control” Journal of Intelligent & Fuzzy Systems, vol. 32, No.6,. 2017.
  21. T.Y. Abdalla, HA Hairik, AM Dakhil , “Minimization of torque ripple in DTC of induction motor using fuzzy mode duty cycle controller ”, Energy, Power and Control (EPC-IQ), 1st International Conference on, IEEE 2010.
  22. Z.T. Allawi , Turki Y. Abdalla, "An Optimal Defuzzification Method for Interval Type-2 Fuzzy Logic Control Scheme" , IEEE science and information conference , 2015, London.
  23. Z.T. Allawi , Turki Y. Abdalla, " PSO-optimized type-2 fuzzy logic controller for navigation of multiple mobile robots",‏ IEEE 19th International Conference On Methods and Models in Automation and Robotics (MMAR), 2014.
  24. Z.T. Allawi , Turki Y. Abdalla, "A PSO-optimized reciprocal velocity obstacles algorithm for navigation of multiple mobile robots",  International Journal of Robotics and Automation, Vol. 4, No.1, 2015.
  25. A. Kaur, A. Kaur, "Comparison of Mamdani-Type and Sugeno-Type Fuzzy Inference Systems for Air Conditioning System", International Journal of Soft Computing and Engineering (IJSCE), Vol.02, 2012
  26. Y. Yang, W. Wang, D. J. Yu and G. Ding, "A fuzzy parameters adaptive PID controller design of digital positional servo system", IEEE Proceeding of the First International Conference on Machine Learning and Cybernetics., pp. 310–314, 2002 ,china.
  27. W H Almutar, " Fuzzy Control Schemes for Active Suspension System" M Sc. thesis, university of Basrah, 2015.
  28. K. Watanabe, J. Tang, M. Nakamura, S. Koga and T. Fukuda, “Mobile Robot Control Using Fuzzy-Gaussian Neural Networks", IEEE/RSJ International Conf. on Robots and system, pp.919-925, Japan, 1993.
Index Terms

Computer Science
Information Sciences

Keywords

Mobile Robot Particles Swarm Optimization fuzzy control FOPID Controller Trajectory tracking.

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