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Reseach Article

Article:Design of Controller using Simulated Annealing for a Real Time Process

by S.M GirirajKumar, Bodla Rakesh, N.Anantharaman
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 6 - Number 2
Year of Publication: 2010
Authors: S.M GirirajKumar, Bodla Rakesh, N.Anantharaman
10.5120/1053-1368

S.M GirirajKumar, Bodla Rakesh, N.Anantharaman . Article:Design of Controller using Simulated Annealing for a Real Time Process. International Journal of Computer Applications. 6, 2 ( September 2010), 20-25. DOI=10.5120/1053-1368

@article{ 10.5120/1053-1368,
author = { S.M GirirajKumar, Bodla Rakesh, N.Anantharaman },
title = { Article:Design of Controller using Simulated Annealing for a Real Time Process },
journal = { International Journal of Computer Applications },
issue_date = { September 2010 },
volume = { 6 },
number = { 2 },
month = { September },
year = { 2010 },
issn = { 0975-8887 },
pages = { 20-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume6/number2/1053-1368/ },
doi = { 10.5120/1053-1368 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:54:22.487870+05:30
%A S.M GirirajKumar
%A Bodla Rakesh
%A N.Anantharaman
%T Article:Design of Controller using Simulated Annealing for a Real Time Process
%J International Journal of Computer Applications
%@ 0975-8887
%V 6
%N 2
%P 20-25
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Proportional Integral Derivative Controllers have dominated the industries for nearly a century owing to their simplicity, flexibility and efficiency. The demand for developing new algorithms for designing these controllers to cope up with the complexities of the constantly evolving industries have turned the attention of the designers towards evolutionary algorithms like Simulated Annealing(SA). This paper compares the tuning of the PID controllers using SA and traditional methods. The results obtained reflect that using SA tuned controllers improve the performance of the process in terms of time domain and frequency domain specifications. Further the disturbance rejection as well as set-point tracking is being improved with a considerable enhancement in stability of the process.

References
  1. Hsien-Yu Tseng and Chang-Ching Lin, "A simulated annealing approach for curve fitting in automated manufacturing systems", Journal of Manufacturing technology management, Vol 18, No.2 pp. 202-216, 2007
  2. PierpaoloCaricato and Antonio Grieco, “Using simulated annealing to design a material handling system”, IEEE intelligent systems, 2005.
  3. Li-Sun Shu, Shinn-Ying Ho and Shinn-Jang Ho, “A novel orthogonal simulated annealing algorithm for optimization of electromagnetic problems.”, IEEE transactions on Magnetics, Vol.40, No. 4, July 2004.
  4. SigurdSkogestad, “Simple analytic rules for model reduction and PID controller tuning”, Journal of Process Control 13 (2003) 291–309,2003.
  5. L.R.Varela, R.A.Ribeiro and F.M.Pires, “Simulated annealing and fuzzy optimization”, Proceedings of the 10th Mediterranean conference on control and automation- MED2002,Portugal, July 9-12, 2002.
  6. JavedAlam Jan and BohumilSulc, “Evolutionary computing methods for optimizing virtual reality process models”, International Carpathian control conference ICCC’2002, Malenovice Czech republic, May 27-30, 2002.
  7. S.Chen, R.H. Istepanian and J.Wu, “ Optimizing stability bounds of finite-precision PID controllers using adaptive simulated annealing”, Proceedings of the American control conference ,San Diego, California ,June 1999.
  8. S. Chen and B.L.Luk, "Adaptive simulated annealing for optimization in signal processing applications", Journal of Engineering and electronics, Vol. 79,pp. 117-128, 1999.
  9. Yan Tian, Li Erxue and Yang Shiyou, “Improved simulated annealing algorithm and its application in fault-location of power transmission lines”, IEEE 1998.
  10. Luyben, W.L and M.L Luyben, “Essentials of process control”, McGraw-Hill, New York (1997).
  11. Simon Fabri and VisakanKadirkamanathan, “Dynamic structure neural networks for stable adaptive control of nonlinear systems”, IEEE transactions on neural networks, Vol 7, No. 5, September1996.
  12. Sanjay I. Mistry, Shao-liang Chang and Satish S. Nair, “Indirect control of a class of nonlinear dynamic systems”, IEEE transactions on neural networks Vol 7, No. 4, July 1996.
  13. Mehrdad Salami and Greg Cain, “An adaptive PID controller based on Genetic algorithm processor”, Genetic algorithms in engineering systems:Innovations and applications 12-14 September 1995, Conference publication No. 414, IEE 1995.
  14. Su Whan Sung, In-Beum Lee and Jitae Lee,“ Modified Proportional-Integral Derivative (PID) Controller and a New Tuning Method for the PID Controller”,Ind. Eng.Chem. Res.,34, 4127-4132, 1995.
  15. Sundaresan,K.R.,Krishnaswamy,R.R.,“Estimation of time delay, time constant parameters in Time, Frequency and Laplace Domains”, Journal of Chemical Engineering.,56,257,1978.
  16. J. G. Ziegler and N. B. Nichols, “Optimum settings for automatic controllers,” Trans. Amer. Soc. Mech. Eng., vol. 64, pp. 759–768, 1942
Index Terms

Computer Science
Information Sciences

Keywords

PID tuning Modeling Process Control Evolutionary algorithm SA