Cover
Vol. 10 No. 1 (2010)

Published: June 30, 2010

Pages: 54-65

Original Article

Genetic Algorithm Based Optimal Design of a PlD Controller for Trajectory Tracking of a Mobile Robot

Turki Y. Abdalla 1 Seaar J. AI_Duboni 2
1 Department of Computer Engineering University of Basrah, Basrah,Iraq
2 Department of Computer Engineering University of Basrah, Basrah, Iraq
History
  • Received: March 30, 2010
  • Available Online: June 30, 2010
DOI

https://doi.org/10.33971/bjes.10.1.6

Abstract

This paper deals with the modeling and control strategics of the motion of wheeled mobile robot. The model of the mobile robot has two driving wheels and the azimuth and velocity are dependently controlled by two PID controllers. The PID controller is one of the earliest and famous industrial controllers. It has many advantages: It is economic, simple easy to be tuned and robu.~t. The tuning of these controllers is governed by system nonlinearities and continuous parameter variations. lbis paper deals with the optimal design of a PID controller for path tracking of mobile robot by using genetic algorithms (GA). The designed controller is tested for different paths.

Keywords

References

  1. Y. Shinoda, "Collaborative Motion Planning of Autonomous Robots", M.Sc. Thesis, School of Information Science, Advanced Institute of Science and Technology, Ishikawa Japan, 2007.
  2. R. A. Felder, "Mobile Robot Simulation of Clinical Laboratory Deliveries", M.Sc. Thesis, the University of Virginia, U.S.A, 1998.
  3. A. Haj-Ali and H. Ying, "Structural Analysis of Fuzzy Controllers with Nonlinear Input Fuzzy Sets in Relation to Nonlinear PID Control with Variable Gains", Wayne State University, Detroit, MI, 2004.
  4. S. M. Gadoue, D. G. and J. W. Finch, "Tuning of PI Speed Controller in DTC of Induction Motor Based on Genetic Algorithms and Fuzzy Logic Schemes", International Journal of Advanced Robotic Systems, University of Newcastle upon Tyne, pp. 187-194, 2005.
  5. W. Gharieb, O. Nagib, "Fuzzy Intervention in PID Controller Design", IEEE International Symposium on Industrial Electronics, Pusan KOREA, June 2001.
  6. J. Jantzen, "Tuning of Fuzzy PID Controllers", Technical University of Denmark, Dept. of Automation, report no 98-H871, Sep 1998.
  7. A. N. I. Wardana, "PID-Fuzzy Controller for Grate Cooler in Cement Plant", Indonesia Cement and Concrete Institute, Bogor, 1997.
  8. J. A. Shaw, "The PID Control Algorithm, How it works, how to tune it, and how to Proc.", IEEE Congress on Evolutionary Computation, Edinburgh, UK, 2003.
  9. P. J. Fleming and R. C. Purshouse, "Genetic Algorithms in Control Systems Engineering", University of Sheffield, Research Report No. 789, May 2001.
  10. H. C. Chen and S. H. Chang, "Genetic Algorithms Based Optimization Design of a PID Controller for an Active Magnetic Bearing", International Journal of Computer Science and Network Security, VOL.6 No.12, December 2006.
  11. F. Xhafa, "An Experimental Study on GA Replacement Operators for Scheduling on Grids", Technical University of Catalonia, Barcelona, Spain, pp. 927-932, 2004.
  12. A. Albagul and Wahyudi, "Dynamic Modelling and Adaptive Traction Control for Mobile Robots", International Journal of Advanced Robotic Systems, Volume 1, Number 3, pp. 149-154, 2004.
  13. X. Jiang and Y. M. Xingquan, "Predictive Fuzzy Logic Controller for Trajectory Tracking of a Mobile Robot", IEEE Mid-Summer Workshop on Soft Computing in Industrial Applications, Helsinki University of Technology, June 2005.
  14. S. E. Mahmoudi, A. A. Bitaghsir, R. Forouzandeh and A. R. Marandi, "A New Genetic Method for Mobile Robot Navigation", Electrical and Computer Engineering Dep. University of Tehran, IRAN, September 2004.
  15. V. Mohan Peri and D. Simon, "Fuzzy Logic Control for an Autonomous Robot", M.Sc. Thesis, Cleveland State University, Ohio, USA, 2002.
  16. J. Peng, Y. Wang and W. Sun, "Trajectory-Tracking Control for Mobile Robot Using Recurrent Fuzzy Cerebellar Model Articulation Controller", Neural Information Processing - Letters and Reviews, Vol. 11, No. 1, January 2007.
  17. H. C. Chen and S. H. Chang, "Genetic Algorithms Based Optimization Design of a PID Controller for an Active Magnetic Bearing", International Journal of Computer Science and Network Security, VOL.6, No.12, December 2006.
  18. F. Peter, P. Hartmut and F. Carlos, "GEATbx Introduction: Evolutionary Algorithms: Overview, Methods and Operators", M.Sc. Thesis, University of Sheffield, November 2005.
  19. Genetic Algorithm Toolbox for Matlab, Help file for Matlab, version (7.6.0) R2008a.
  20. G. Boker and S. Bin, "The PID Controller Design Using Genetic Algorithm", M.Sc. Thesis, University of Southern Queensland, October 2005.
  21. G. Mester, "Obstacle Avoidance of Mobile Robots in Unknown Environments", International Symposium on Intelligent Systems and Informatics, Subotica, Serbia, pp. 128-139, August 2007.