Fuzzy Self-tuning of Conventional PID Controller for High-Order Processes

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 247)


We propose an improved auto-tuning Ziegler-Nichols PID (ZNPID) controller. The proposed controller is a Fuzzy self-tuning ZNPID controller (FST-ZNPID). Conventional Ziegler-Nichols tuned PI and PID controllers provide poor performance for non-linear and high-order systems. In FST-ZNPID enhanced performance is obtained by continuous modification of the proportional constant depending on the process trend. In the proposed FST-ZNPIDC an online auto-tuning factor ‘α’ is incorporated, which is derived by firing 25 fuzzy rules defined on the process error and change of error. Performance of the proposed controller (FST-ZNPID) is tested and compared with other reported works for high-order linear and non-linear dead time systems under both set point change and load disturbance. The developed controller is found to be robust with considerable changes in the process dead time.


PID controller Ziegler-Nichols tuning Auto-tuning Self-tuning fuzzy controller 


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  1. 1.
    Shinsky, F.G.: Process control systems — application, design, and tuning. McGraw-Hill, New York (1998)Google Scholar
  2. 2.
    Astrom, K.J., Hang, C.C., Person, P., Ho, W.K.: Towards intelligent PID control. Automatica 28(1), 1–9 (1992)CrossRefGoogle Scholar
  3. 3.
    Seborg, D.E., Edgar, T.F.: Adaptive control strategies for process control: A survey. AICHE J. 32(6), 881–913 (1986)CrossRefGoogle Scholar
  4. 4.
    Kristiansson, B., Lennartson, B.: Robust and optimal tuning of PI and PID controllers. IEE Proc. Control Theory Appl. 149(1), 17–25 (2002)CrossRefGoogle Scholar
  5. 5.
    Dey, C., Mudi, R.K.: An improved auto-tuning scheme for PID controllers. ISA Trans. 48(4), 396–409 (2009)CrossRefGoogle Scholar
  6. 6.
    Mudi, R.K., Dey, C.: Performance improvement of PI controllers through dynamic set-point weighting. ISA Transactions 50, 220–230 (2011)CrossRefGoogle Scholar
  7. 7.
    Dey, C., Mudi, R.K., Lee, T.T.: Dynamic set-point weighted PID controller. Control and Intelligent Systems 37(4), 212–219 (2009)Google Scholar
  8. 8.
    Mudi, R.K., Dey, C., Lee, T.T.: An improved auto-tuning scheme for PI controllers. ISA Transactions 47, 45–52 (2008)CrossRefGoogle Scholar
  9. 9.
    Mudi, R.K., Pal, N.R.: A robust self-tuning scheme for PI and PD type fuzzy controllers. IEEE Trans Fuzzy Syst. 7(1), 2–16 (1999)CrossRefGoogle Scholar
  10. 10.
    Mudi, R.K., De Maity, R.R.: A Noble Fuzzy Self-Tuning Scheme for Conventional PI Controller. In: Satapathy, S.C., Udgata, S.K., Biswal, B.N. (eds.) Proceedings of Int. Conf. on Front. of Intell. Comput. AISC, vol. 199, pp. 83–91. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  11. 11.
    Mudi, R.K., Pal, N.R.: A self-tuning fuzzy PD controller. IETE J. Res. 44(4-5), 177–189 (1998)Google Scholar
  12. 12.
    Mudi, R.K., Pal, N.R.: A Self-Tuning Fuzzy PI Controller. Fuzzy Sets and Systems 115, 327–338 (2000)CrossRefMATHGoogle Scholar
  13. 13.
    Ziegler, J.G., Nichols, N.B.: Optimum settings for automatic controllers. ASME Trans. 64, 759–768 (1942)Google Scholar

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© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Dept. of Electronics & Instrumentation EngineeringDr. B.C. Roy Engineering CollegeDurgapurIndia
  2. 2.Dept. of Instrumentation & Electronics EngineeringJadavpur UniversityKolkataIndia

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