CFP last date
20 January 2025
Reseach Article

Comparative Analysis of Fuzzy Logic based Conventional PID Controller for Second Order System with Dead Time

Published on September 2016 by Kuldeep Kaur, Gurwinder Kaur
International Conference on Advances in Emerging Technology
Foundation of Computer Science USA
ICAET2016 - Number 3
September 2016
Authors: Kuldeep Kaur, Gurwinder Kaur
16c82c4c-4a09-4a14-8795-3a618124de33

Kuldeep Kaur, Gurwinder Kaur . Comparative Analysis of Fuzzy Logic based Conventional PID Controller for Second Order System with Dead Time. International Conference on Advances in Emerging Technology. ICAET2016, 3 (September 2016), 21-25.

@article{
author = { Kuldeep Kaur, Gurwinder Kaur },
title = { Comparative Analysis of Fuzzy Logic based Conventional PID Controller for Second Order System with Dead Time },
journal = { International Conference on Advances in Emerging Technology },
issue_date = { September 2016 },
volume = { ICAET2016 },
number = { 3 },
month = { September },
year = { 2016 },
issn = 0975-8887,
pages = { 21-25 },
numpages = 5,
url = { /proceedings/icaet2016/number3/25893-t045/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Emerging Technology
%A Kuldeep Kaur
%A Gurwinder Kaur
%T Comparative Analysis of Fuzzy Logic based Conventional PID Controller for Second Order System with Dead Time
%J International Conference on Advances in Emerging Technology
%@ 0975-8887
%V ICAET2016
%N 3
%P 21-25
%D 2016
%I International Journal of Computer Applications
Abstract

This paper deals with the design of a fuzzy PID Controller (FPIDC) with dynamic gain through a fuzzy scheme. The gain factor of Proportional, Integral and Derivative is varied according to process of the proposed dead time. FPIDC is modified which depends on the normalized change of error of the controlled variable (ec) and its number of fuzzy partitions. The proposed scheme is tested for a wide variety of second-order systems with different dead-time (L) under both set-point change and load disturbance. Detailed performance comparison with a well-known fuzzy PD controller and fuzzy PID controller reported in the leading literature is provided with respect to a number of performance indices. The proposed controller is designed using a very simple control rule–base having seven rules and triangular membership functions. Simulation results justify the effectiveness of the proposed scheme. The simulation results under MATLAB environment has predicted better performance with fuzzy PID controller with different values of Dead Time under all operating conditions of the drive. In results, Conventional PID Controller and Fuzzy Logic Based Controller implemented on first order and second order systems. The step input is taken as the reference input to obtain the transient and steady state response of the systems. The terms like peak time, maximum overshoot, settling time, rise time, Sum Squared Error (SSE), Integral Absolute Error (IAE) and Integral Absolute Time Multiplied Error (IATE) and sum square error are calculated and compared.

References
  1. S. Singh, R. Mitra, IEEE Proceedings, 31 (2014).
  2. S. Mukherjee, S. Pandey, S. Mukhopadhyay, N. B. Hui, IEEE National Conference of Computer Science, 12 (2014).
  3. E. Dincel, U. Yildirm, M. T. Soylemez, IEEE International Conference on Control System, Computing and Engineering, 21 (2013).
  4. M. Chaturvedi, P. Juneja, IEEE International Conference on Advanced Electronic Systems (ICAES), 13 (2013).
  5. C. Dey, R. K. Mudi, P. K. Paul, IEEE 7th International Conference on Electrical and Computer Engineering, 11 (2012).
  6. R. Arulmozhiyal, R. Kandiban, IEEE International Conference on Computer Communication and Informatics (ICCCI), 27 (2012).
  7. R. K. Mudi, R. R. De, A. A. Pal, IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCl), 42 (2012).
  8. K. Sinthipsomboon, W. Pongaen, P. Pratumsuwan, IEEE 6th Conference on Industrial Electronics and Applications, 67 (2011).
  9. R. Bandyopadhyay, D. Patranabis, Elsevier ISA Transactions, 40 (2001).
  10. N. R. Pal, R. K. Mudi, IEEE Transactions on Fuzzy Systems, 7 (1999).
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy Logic Controller Scaling Factor Non Linear Proportional Derivative Controller Proportional Integral Derivative Controller