A hybrid frequency—time domain adaptive fuzzy control scheme for flexible link manipulators | Journal of Intelligent & Robotic Systems Skip to main content
Springer Nature Link
Log in

A hybrid frequency—time domain adaptive fuzzy control scheme for flexible link manipulators

  • Published:
Journal of Intelligent and Robotic Systems Aims and scope Submit manuscript

Abstract

This paper addresses the implementation of an adaptive fuzzy controller for flexible link robot arms. The design technique is a hybrid scheme involving both frequency and time domain techniques. The eigenvalues of the open loop plant can be estimated through application of a frequency domain based identification algorithm. The region of the eigenvalue space, within which the system operates, is partitioned into fuzzy cells. Membership function are assigned to the fuzzy sets of the eigenvalue universe of discourse. The degree of uncertainty on the estimated eigenvalues is encountered through these membership functions. The knowledge data base consists of feedback gains required to place the closed loop poles at predefined locations. A rule based controller infers the control input variable weighting each with the value of the membership functions at the identified eigenvalue. The afore-mentioned controller is compared through simulation with conventional techniques, namely pole placement and gain scheduling.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Daley, S. and Gill, K. F.: Comparison of a fuzzy logic controller with aP +D control law,ASME Dynamic Sys. Meas. Control 111 (1989), 128–137.

    Google Scholar 

  2. Dote, Y.: Stability analysis of variable-structured PI controller by fuzzy logic for servo system, inProc. IEEE Conf. Decision and Control, Brighton, England, December 1991, pp. 1217–1218.

  3. Kiska, J. B., Gupta, M. M., and Nikiforuk, P. N.: Energistic stability of fuzzy dynamic systems,IEEE Trans. Systems Cybernet. 4(5) (1985), 783–792.

    Google Scholar 

  4. Kang, H. and Vachtsevanos, G.: Model reference fuzzy control, inProc. IEEE Conf. Decision and Control, Tampa, FL, December 1989, pp. 751–756.

  5. Lee, C. C.: Fuzzy logic in control Systems: fuzzy logic controller, Part I,IEEE Trans. Systems Man Cybernet. 20(2) (1990), 404–418.

    Google Scholar 

  6. Lee, C. C.: Fuzzy logic in control systems: fuzzy logic controller, Part II,IEEE Trans. Systems Man Cybernet. 20(2) (1990), 419–435.

    Google Scholar 

  7. Mamdani, E. H.: Application of fuzzy algorithms for simple dynamic plant,Proc. IEE, Part D121(12) (1974), 1585–1588.

    Google Scholar 

  8. Paraskevopoulos, P. N.: On the pole assignment by proportional plus derivative output feedback,Electronic Lett. 14 (1976), 34–35.

    Google Scholar 

  9. Pedrycz, W.: An approach to the analysis of fuzzy systems,Internat. J. Control 34(3) (1981), 403–421.

    Google Scholar 

  10. Rutherford, D. A. and Bloore, G. C.: The implementation of fuzzy algorithms for control,Proc. IEEE 64(4) (1976), 572–573.

    Google Scholar 

  11. Ray, K. S. and Majumber, D. D.: Application of stability criteria for stability analysis of linear SISO and MIMO systems associated with fuzzy logic controller,IEEE Trans. Systems Man Cybernet. 3(2) (1984), 345–349.

    Google Scholar 

  12. Shynk, J. J.: Adaptive IIR filtering,IEEE ASSP Magazine 6(2) (1989), 4–21.

    Google Scholar 

  13. Tang, K. L. and Mulholland, R. J.: Comparing fuzzy logic with classical controller designs,IEEE Trans. Systems Man Cybernet. 17(6) (1987), 1085–1087.

    Google Scholar 

  14. Takagi, T. and Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control,IEEE Trans. Systems Man Cybernet. 15(1) (1985), 116–132.

    Google Scholar 

  15. Tzes, A. and Yurkovich, S.: A frequency domain identification scheme for flexible structure control,Trans. ASME J. Dyn. Meas. Control 112 (1990), 427–434.

    Google Scholar 

  16. Tzes, A. and Yurkovich, S.: An adaptive input shaping control scheme for vibration supression in slewing flexible structures,IEEE Trans. Control Systems Technol. 1 (June 1993).

  17. Tzes, A.:Self-tuning controllers for flexible link manipulators, PhD thesis, The Ohio State University, 1990.

  18. Wang, B. H. and Vachtsevanos, G.: Fuzzy logic control: A systematic design methodology, inProc. IEEE Conf. Decision and Control, Brighton, England, December 1991, pp. 1219–1220.

  19. Zadeh, L. A.: Fuzzy sets as a basis for a theory of possibility,Fuzzy Sets Systems 1(1) (1978), 3–28.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Polytechnic University, 333 Jay Street, 11201, Brooklyn, NY, USA

    Anthony Tzes & Kyriakos Kyriakides

Authors
  1. Anthony Tzes
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kyriakos Kyriakides
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tzes, A., Kyriakides, K. A hybrid frequency—time domain adaptive fuzzy control scheme for flexible link manipulators. J Intell Robot Syst 10, 283–300 (1994). https://doi.org/10.1007/BF01258262

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01258262

Key words

Search

Navigation