6 Conclusion
In this paper, several design procedures presented in the process control literature for the PID controller, based on fuzzy control systems, are reviewed.
In order to make the fuzzy logic control less dependent on the quality of the expert knowledge, four techniques for improving the fuzzy PID controllers performance, by adding some kind of adaptation feature when facing nonlinear processes, were presented.
From simulation results, it was possible to show that all four adaptive controllers had better responses than the FPID controller. Adaptive fuzzy PID controllers had a smooth response and a more conservative control action than the non-adaptive fuzzy PID controller.
As a future work, the next step is to assess the adaptive fuzzy PID system on a nonlinear experimental setup. Other fuzzy control systems combined with advanced control techniques, such as, auto-tuning, minimum variance and predictive strategies are also some future considerations.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
K. J. Åström and T. Hägglund, “The future of PID control”, Control Engineering Practice, Vol. 9, pp. 1163–1175, 2001.
K. J. Åström and B. Wittenmark, Adaptive Control, Addison-Wesley, New York, 1995.
E. Mamdani and S. Assilian, “An experiment in linguistic synthesis of a fuzzy logic controller”, Int. Journal of Man-Machine Studies, Vol. 7, No. 1, pp. 1–13, 1975.
F. Mrad and G. Deeb, “Experimental comparative analysis of adaptive fuzzy logic controllers”, IEEE Trans. on Control Systems Technology, Vol. 10, pp. 250–255, 2002.
T. C. Minh and L. H. Hoang, “Model reference adaptive fuzzy controller and fuzzy estimator for high performance induction motor drives”, Proc. Annu. Meet. IEEE Ind. Applicat. Soc., pp. 380–387, 1996.
Y. F. Li and C. C. Lau, “Development of fuzzy algorithms for servo systems”, IEEE Control Systems Magazine, April, pp. 65–72, 1989.
L. S. Coelho and A. A. R. Coelho, “An experimental and comparative study of PID control structures”, Advances in Soft Computing: Engineering Design and Manufacturing, Springer, London, pp. 147–159, 1999.
D. P. Kwok, P. Tam, C. K. Li and P. Wang. “Linguistic PID controllers”, 11th IFAC World Congress, Tallin, Estonia, USSR, Vol. 7, pp. 192–197, 1990.
H. X. Li and H. B. Gatland, “Enhanced methods of fuzzy logic control”, Proceedings of FUZZY-IEEE/IFES’95, Yokohama, Japan, Vol. 1, pp. 331–336, 1995.
H. A. Malki, D. Misir, D. Feigenspan and G. Chen, “Fuzzy PID control of a flexible-joint robot arm with uncertainties from time-varying loads”, IEEE Transactions on Control Systems Technology, Vol. 5, pp. 371–378, 1997.
W. Li, “Design of a hybrid fuzzy logic proportional plus conventional integral-derivative controller”, IEEE Transactions on Fuzzy Systems, Vol. 6, pp. 449–463, 1998.
M. Golob, “Decomposed fuzzy proportional-integral-derivative controllers”, Applied Soft Computing, Vol. 18, pp. 1–14, 2001.
Y. S. Kung and C. Liaw, “A fuzzy controller improving a linear model following controller for motor drives”, IEEE Trans. Fuzzy Syst., Vol. 2, pp. 194–202, 1994.
J. R. Layne and K. M. Passino, “Fuzzy model reference learning control”, Journal of Intelligent and Fuzzy Systems, Vol. 4, pp. 33–47, 1996.
N. K. A. Rashid and A. S. Heger, “Tuning of fuzzy logic controllers by parameter estimation method”, Fuzzy Logic and Control: Software and Hardware Applications, Prentice-Hall, pp. 374–392, 1993.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Callai, T., Santos, J., Sumar, R., Coelho, A. (2005). Applying the Potentiality of Using Fuzzy Logic in PID Control Design. In: Hoffmann, F., Köppen, M., Klawonn, F., Roy, R. (eds) Soft Computing: Methodologies and Applications. Advances in Soft Computing, vol 32. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32400-3_15
Download citation
DOI: https://doi.org/10.1007/3-540-32400-3_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25726-4
Online ISBN: 978-3-540-32400-3
eBook Packages: EngineeringEngineering (R0)