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Reseach Article

Optimizing Azadi Controller with COA

by Ashkan Aghaei, Sassan Azadi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 61 - Number 8
Year of Publication: 2013
Authors: Ashkan Aghaei, Sassan Azadi
10.5120/9949-4594

Ashkan Aghaei, Sassan Azadi . Optimizing Azadi Controller with COA. International Journal of Computer Applications. 61, 8 ( January 2013), 22-26. DOI=10.5120/9949-4594

@article{ 10.5120/9949-4594,
author = { Ashkan Aghaei, Sassan Azadi },
title = { Optimizing Azadi Controller with COA },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 61 },
number = { 8 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 22-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume61/number8/9949-4594/ },
doi = { 10.5120/9949-4594 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:08:34.872973+05:30
%A Ashkan Aghaei
%A Sassan Azadi
%T Optimizing Azadi Controller with COA
%J International Journal of Computer Applications
%@ 0975-8887
%V 61
%N 8
%P 22-26
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cuckoo Optimization Algorithm (COA) is one of the hottest meta-heuristic algorithms. Finding the best optimal point, rapid convergence, simplicity in determining algorithm parameters are some merits of COA. Azadi controller is one of latest method of adaptive controlling. It is simple, robust, effective and immune against noise and plant's variations. All of them make it unique and without no compotator. To tune it, there are three parameters. On this paper, COA undertakes responsibility of tuning these parameters to achieve the best response. Catalytic Continuous Stirred Tank Reactor (CSTR) is an ordinary industrial system and it is a decent example to survey Azadi controller that is designed by COA.

References
  1. S. Azadi, A. Aghaei and M. A. Hajimousa, "Comparing Azadi Controller with Several Optimal Controllers", Journal of Basic and Applied Scientific Research (JBASR), vol. 1, no. 2, February 2013
  2. S. Azadi, A. Nikkerdar and M. Nouri, "Utilizing Azadi Controller (Positive Feedback) to Suppress the Vibrations of a DC Motor",Journal of Basic and Applied Scientific Research, pp. 10498-10507, 2012.
  3. S. Azadi, "Presenting an Adaptive Controller Based on Positive Feedback"in ICAFS, Prague, Czech. , 2010, 27-29August.
  4. S. Azadi, "Utilizing an Adaptive Controller (Azadi Controller) for Trajectory Planning of PUMA 560 Robot",in 2011 International Conference on Robotics and Cybernetics (ICCRC 2011), New Delhi,21-23 March 2011.
  5. S. Azadi, "Introducing a Simple Adaptive Controller (Azadi Controller) Based on Positive Feedbacks", Mianyang, CHINA, 2011 Chinese Control and Decision Conference (CCDC 2011), 23-25 May 2011.
  6. S. A. Mazhari i S. Kumar, "Heuristic Search Algorithms for Tuning PUMA 560 Fuzzy PID Controller",International Journal of Computer Science, fall 2008.
  7. R. Tanscheit and E. Lembessis, "On the behavior and tuning of a fuzzy rulebased self-organizing controller", in Mathematics of the analysis and design of process control, vol. 1, Amsterdam, Elsevier Science Publishers. , 1992, p. 603–612.
  8. K. Ahn, D. Truong i Y. Soo, "Self tuning fuzzy PID control for hydraulic load simulator Automation and Systems" in IEEE International Conference on Control, Korea, 2007.
  9. E. Gonda, H. Miyata i M. Ohkita, "Self-tuning of fuzzy rules when learning data have a radically changing distribution", Electrical Engineering in Japan, vol. 144, nr 4, p. 63–74, 2003.
  10. F. Guely i P. & Siarry, "Gradient descent method for optimizing various fuzzy rule bases",in Second IEEE international conference on fuzzy systems, 1993.
  11. P. Seihwan i H. Lee-kwang, "Designing fuzzy logic controllers by genetic algorithms considering their characteristics",in Congress on Evolutionary Computation, 2000.
  12. Y. C. Chiou i L. W. Lan, "Genetic fuzzy logic controller: an iterative evolution algorithm with new encoding method", Fuzzy Sets and Systems, nr 152, p. 617–635, 2005.
  13. R. Alcala, J. Benitez, J. Casillas, O. Cordon i R. Perez, "Fuzzy control of HVAC systems optimized by genetic algorithms", Applied Intelligence, vol. 2, nr 18, p. 155 – 177, 2003.
  14. F. Herrera, M. Lozano i J. L. Verdegay, "Tuning fuzzy logic controllers by genetic algorithms", International Journal of Approximate Reasoning, vol. 12, p. 299–315, 1995.
  15. A. Homaifar i E. McCormick, "Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms", IEEE Transactions on Fuzzy Systems, vol. 3, nr 2, p. 129–139, 1995.
  16. H. Gurocak, "Genetic-algorithm-based method for tuning fuzzy logic controllers", Fuzzy Sets and Systems, vol. 108, nr 1, p. 39–47, Nov. 1999.
  17. H. Youssef, S. Sait i S. Khan, "Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm", Eng. Appl. Artif. Intell. , vol. 15, p. 327–340, 2002.
  18. L. Ingber i B. Rosen, "Genetic algorithms and very fast simulated reannealing", A comparison. Mathematical and Computer Modeling, vol. 16, nr 11, pp. 87-100, 1992.
  19. G. Liu i W. Yang, "Learning and tuning of fuzzy membership functions by simulated annealing algorithm", in IEEE Asia–Pacific conference on circuits and systems, 2000.
  20. W. Lei, K. Qi i W. Qidi, "Fuzzy logic based multi-optimum programming in particle swarm optimization", w IEEE International Conference on Networking, Sensing and Control, Tucson, Arizona, USA, 2005.
  21. H. -M. Feng, "Self-generation fuzzy modeling systems through hierarchical recursive-based particle swarm optimization", Cybernet. Syst. : Int. J. , nr 36, p. 623–639, 2005.
  22. Q. Kang, L. Wang i Q. Wu, "Research on fuzzy adaptive optimization strategy of particle swarm algorithm", Int. J. Inform. Technol. , vol. 12, nr 3, p. 66–76, 2006.
  23. W. Pang, K. -p. Wang, C. -g. Zhou i L. -j. Dong, "Fuzzy discrete particle swarm optimization traveling salesman problem",w Fourth International Conference on Computer and Information Technology, 2004.
  24. R. Rajabioun, "Cuckoo Optimization Algorithm", Applied Soft Computing, pp. 5508-5518, 13 May 2011.
  25. Artur C. Guyton, "Textbook of Medical Physiology", W. B. Saunders Company.
  26. Eric R. Kandel, James H. Schwartz, 2000, "Principles of Neural Science", Elsevier Science Publishing Company.
  27. "Matlab Help", Mathworks, 2012.
  28. M. Mohammadzaheri, "Double-command fuzzy control of a nonlinear CSTR",in 3rd IEEE Conference on Industrial Electronics and Applications, 2008. ICIEA, Adelaide, 2008.
  29. O. Katsuhico, "Modern Control Engineering".
Index Terms

Computer Science
Information Sciences

Keywords

Azadi controller COA CSTR