Hostname: page-component-cb9f654ff-d5ftd Total loading time: 0 Render date: 2025-08-24T03:16:20.811Z Has data issue: false hasContentIssue false
  • English
  • Français

Using a genetic algorithm to fully optimise a fuzzy logic controller for a two-link-flexible robot arm

Published online by Cambridge University Press:  08 September 2008

V. B. Nguyen  and
A. S. Morris
V. B. Nguyen
Affiliation:
Department of Automatic Control and Systems Engineering, University of Sheffield, UK.
A. S. Morris*
Affiliation:
Department of Automatic Control and Systems Engineering, University of Sheffield, UK.
*
*Corresponding author: E-mail: a.morris@sheffield.ac.uk
Get access Rights & Permissions [Opens in a new window]

Summary

Flexible manipulators have received wide attention because they surpass their rigid counterparts in many criteria. Unfortunately, traditional controller design methods for flexible arms implemented by human experts are usually tedious and intractable. In order to improve system behaviour, this paper proposes schemes based on genetic algorithms (GAs) which optimise the parameters of a fuzzy logic controller for a robotic manipulator with two-link flexibility and two-joint elasticity. Two alternative GA-optimised schemes are simulated and their control behaviour is compared with that of human-expert-designed controller.

Keywords

Flexible manipulatorFuzzy logic controllerGenetic algorithmOptimisation

Information

Type
Article
Information
Robotica , Volume 27 , Issue 5 , September 2009 , pp. 677 - 687
Copyright
Copyright © Cambridge University Press 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

1. Tadikonda, S. S. K., Mordfin, T. G. and Hu, T. G., “Assumed modes method and articulated flexible multibody dynamics,” J. Guidance, Control, Dyn. 18 (3), 404–410 (1995).CrossRefGoogle Scholar
2. Karray, F., Tafazolli, S. and Guealed, W., “Robust tracking of a lightweight manipulator system,” Nonlinear Dyn. 20 (2), 169–179 (1999).CrossRefGoogle Scholar
3. Martins, J., Botto, M. A. and Costa, J. S. D., “Modeling of flexible beams for robotic manipulators,” Multibody Syst. Dyn. 7 (1), 79–100 (2002).CrossRefGoogle Scholar
4. Naganathan, G. and Soni, A. H., “Coupling effects of kinematics and flexibility in manipulators,” Int. J. Rob. Res. 6, 75–84 (1987).CrossRefGoogle Scholar
5. Ge, S. S., Lee, T. H. and Zhu, G., “A nonlinear feedback controller for a single-link flexible manipulator based on a finite element model,” J. Rob. Syst. 14 (3), 165–178 (1997).3.0.CO;2-P>CrossRefGoogle Scholar
6. Theodore, R. and Ghosal, A., “Comparison of the assumed modes and finite element models for flexible multi-link manipulators,” Int. J. Rob. Res. 14 (2), 91–111 (1995).CrossRefGoogle Scholar
7. Subudhi, B. and Morris, A. S., “Singular perturbation approach to trajectory tracking of flexible robot with joint elasticity,” Int. J. Syst. Sci. 34, 167–179 (2003).CrossRefGoogle Scholar
8. Moudgal, V. G., Kwong, W. A., Passino, K. M. and Yurkovich, S., “Fuzzy learning control for a flexible-link robot,” IEEE Trans. Fuzzy Syst. 3, 199–210 (1995).CrossRefGoogle Scholar
9. Sooraksa, P. and Chen, G., “Mathematical modeling and fuzzy control of a flexible-link robot arm,” Math. Comput. Model. 27, 73–93 (1998).CrossRefGoogle Scholar
10. Lin, J., “Hierarchical fuzzy logic controller for a flexible link robot arm performing constrained motion tasks,” IEE Proc. Control Theory Appl. 150, 355–364 (2003).CrossRefGoogle Scholar
11. Green, A. and Sasiadek, J. Z., “Adaptive control of a flexible robot using fuzzy logic,” J. Guidance, Control, Dyn. 28, 36–42 (2005).CrossRefGoogle Scholar
12. Yeşildirek, A., Vandegrift, M. W. and Lewis, F. L., “A neural network controller for flexible-link robots,” J. Intell. Rob. Syst. 17, 327–349 (1996).CrossRefGoogle Scholar
13. Talebi, H. A., Patel, R. V. and Asmer, H., “Neural network based dynamic modeling of flexible-link manipulators with application to the SSRMS,” J. Rob. Syst. 17, 385–401 (2000).3.0.CO;2-3>CrossRefGoogle Scholar
14. Li, Y., Liu, G., Hong, T. and Liu, K., “Robust control of a two-link flexible manipulator with quasi-static deflection compensation using neural networks,” J. Intell. Rob. Syst. 44, 263–276 (2005).CrossRefGoogle Scholar
15. Holland, J. H., Adaptation in Natural and Artificial Systems (Ann Arbor, MI: University of Michigan Press, 1975).Google Scholar
16. Buckley, J. J., “Fuzzy genetic algorithm and applications,” Fuzzy Sets Syst. 61, 129–136 (1994).CrossRefGoogle Scholar
17. Homaifar, A. and McCormick, E., “Simultaneous design of membership functions and rule sets for fuzzycontrollers using genetic algorithms,” IEEE Trans. Fuzzy Syst. 3, 129–139 (1995).CrossRefGoogle Scholar
18. Gürocak, H. B., “A genetic-algorithm-based method for tuning fuzzy logic controllers,” Fuzzy Sets Syst. 108, 39–47 (1999).CrossRefGoogle Scholar
19. Homaifar, A., Bikdash, M. and Gopalan, V., “Design using genetic algorithms of hierarchical hybrid fuzzy-PID controllers of two-link robotic arms,” J. Rob. Syst. 14, 449–463 (1997).3.0.CO;2-O>CrossRefGoogle Scholar
20. Meirovitch, L., Analytical Methods in Vibrations (New York: Macmillan, 1967).Google Scholar
21. Morris, A. S. and Madani, A., “Quadratic optimal control of a two-link robot manipulator,” Robotica 16, 97–108 (1998).CrossRefGoogle Scholar
22. Fu, K. S., Gonzalez, R. C. and Lee, C. S. G., Robotics: Control, Sensing, Vision and Intelligence (New York: McGraw-Hill, 1987).Google Scholar
23. Lee, M. A. and Takagi, H., “Integrating design stage of fuzzy systems using genetic algorithms,” Second IEEE International Conference on Fuzzy Systems, San Francisco, CA, USA (1993) pp. 612–617.Google Scholar
24. Harris, C. J., Brown, M. and Moore, C. G., Intelligent Control: Aspects of Fuzzy Logic and Neural Nets (Singapore: World Scientific, 1993).CrossRefGoogle Scholar
25. Dadfarnia, M. and Jalili, N., “Lyapunov-based vibration control of translational euler-bernoulli beams using the stabilizing effect of beam damping mechanisms,” J. Vibration Control, 10, 933–961. (2004).CrossRefGoogle Scholar
26. Aoustin, Y. and Chevallereau, C., “The singular perturbation control of a two-flexible-link robot,” Proceedings of IEEE International Conference on Robotics and Automation, Atlanta, GA, USA (1993) pp. 737–742.Google Scholar