Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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Paper Machine Industrial Analysis on Moisture Control Using BF-PSO Algorithm and Real Time Implementation Setup through Embedded Controller

  • Senthil Kumar, M. (Dept. of Electrical and Electronics Engineering, Syed Ammal Engineering College) ;
  • Mahadevan, K. (Dept. of Electrical and Electronics Engineering, PSNA College of Engineering and Technology)
  • Received : 2015.05.23
  • Accepted : 2015.09.14
  • Published : 2016.03.01
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Abstract

Proportional Integral Derivative (PID) controller tuning is an area of interest for researchers in many areas of science and engineering. This paper presents a new algorithm for PID controller tuning based on a combination of bacteria foraging and particle swarm optimization. BFO algorithm has recently emerged as a very powerful technique for real parameter optimization. To overcome delay in an optimization, combine the features of BFOA and PSO for tuning the PID controller. This new algorithm is proposed to combine both the algorithms to get better optimization values. The real time prototype model of paper machine is designed and controlled by using PIC microcontroller embedded with the programming in C language.

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References

  1. M. Aníbal Valenzuela, Senior Member, IEEE, John Martin Bentley, Life Fellow, IEEE, and Robert D. Lorenz, Fellow, IEEE., Estimation of Condensate Inside Dryer Cylinders During Section Shutdown., IEEE T INDU APPLI., vol. 50, no. 3, 1668-1677, 2014. https://doi.org/10.1109/TIA.2013.2283317
  2. Guillermo Ramírez, Member, IEEE, Robert D. Lorenz, Fellow, IEEE, and M. Aníbal Valenzuela, Senior Member, IEEE., Observer-Based Estimation of Modulus of Elasticity for Papermaking Process, IEEE T INDU APPLI., vol. 50, no. 3, 1678-1686, 2014. https://doi.org/10.1109/TIA.2013.2286218
  3. Guillermo Ramírez, Member, IEEE, M. Aníbal Valenzuela, Senior Member, IEEE, andRobert D. Lorenz, Fellow, IEEE., Expert System for the Detection of Condensate Accumulation Inside Dryer Cylinders During Section Starting., IEEE T INDU APPLI., vol. 51, no. 2, 1427-1437, 2015. https://doi.org/10.1109/TIA.2014.2356654
  4. Ola Slätteke., Modeling and control of the paper machine drying section (Sweden by Media-Tryck, Lund University), 2006.
  5. Chang Hoe Heo., Hyunjun Cho & Yeong -Koo Yeo, Dynamic modelling of paper drying processes, KOREAN J CHEM ENG., vol. 28, no. 8, 1651-1657, 2011. https://doi.org/10.1007/s11814-011-0046-0
  6. Shweta goyal., & Rajesh Kumar., ANN Control of paper drying process, International Journal of Application or Innovation in Engineering & Management, vol. 2, no. 7, 100-107, July2013.
  7. Paul C Austin., John Mack., Matthew McEwan., Puya Afshar., Martin Brown., & J Maciejowski., Improved Energy Efficiency in Paper Making Through Reducing Dryer Steam Consumption using Advanced Process Control, Papercon, 1122-1132, 2011.
  8. Karthik, C., Valarmathi, K., & Raja Lakshmi, M., Nonlinear modelling of moisture control of drying process in paper machine, Proc Int conf on modelling optimisation and computing(ICMOC-2012), (Kumarakoil, India), 1104-1111, 2012.
  9. Prabhakar, G., Nedumal Pugazhenthi, P., & Selvaperumal, S., Implementation Analysis of State Space Modeling and Control of Nonlinear Process using PID algorithm in MATLAB and PROTEUS Environment Applied Mechanics and Materials, vol. 573, 297-303, 2014. https://doi.org/10.4028/www.scientific.net/AMM.573.297
  10. Sharma, S. R., Dahikar, P. B., Embedded design of temperature controller using PIC 16F876A for industries and laboratories International Journal of Innovative Research in Computer and Communication Engineering, vol. 1, no. 10, 2414-2422, 2013.
  11. Ahmed, M. A. Haidar., Chellali Benachaiba., Mohamad Zahir., Software interfacing of servo motor with Microcontroller J. Electrical Systems, vol. 1, no. 9, 84-99, 2013.
  12. Venugopal, P., Ajanta Ganguly., Priyanka Singh., Design of tuning methods of PID controller using fuzzy logic. International Journal of Emerging trends in Engineering and Development, vol. 5, no. 3, 239-248, 2013.
  13. Tang, K. S., Kim Fung Man., Guanrong Chen., & Sam Kwong., An Optimal fuzzy PID controller., IEEE T IND ELECTRON, vol. 48, no. 4, 757, 2001. https://doi.org/10.1109/41.937407
  14. Ziegler, J. G., Nichols, N. B., & Rochester, N. Y., TRANSACTIONS OF THE A. S. M. E, 759-765, 1942.
  15. Sharifian, M. B. B., Rahnavard, R., & Delavari, Velocity control of DC Motor based intelligent methods and optimal integral state feedback controller, International Journal of Computer Theory and Engineering, vol. 1, no1 1793-8201, 2009.
  16. Chia-Nan Ko., Chia-Ju Wu., A PSO-Tuning method for design of fuzzy PID controllers J. Vibration and Control, (2007).
  17. Zwe-Lee Gaing., A Particle swarm optimization approach for optimum design of PID Controller in AVR system, IEEE T ENERGY CONVER, vol. 19, no. 2, 384-391, 2004. https://doi.org/10.1109/TEC.2003.821821
  18. Mishra, S., Bhende, C. N., Bacterial Foraging Technique-Based Optimized Active power filter for load compensation, IEEE T POWER DELIVER, vol. 22, no. 1, 457-465, 2007. https://doi.org/10.1109/TPWRD.2006.876651
  19. Tripathy, M., Mishra, S., Bacteria Foraging-Based solution to optimize both real power loss and voltage stability., IEEE T POWER SYST, vol. 22, no. 1, 240-248, 2007. https://doi.org/10.1109/TPWRS.2006.887968
  20. Morteza Eslamian., Seyed Hossein Hosseinian., Behrooz Vahidi., Bacterial Foraging-Based solution to the unit-commitment problem., IEEE T POWER SYST vol. 24, no. 3, 1478-1488, 2009. https://doi.org/10.1109/TPWRS.2009.2021216
  21. Swagatam Das., Sambarta Dasgupta., Arijit Biswas, Ajith Abraham., Amit Konar., On Stability of the chemotactic dynamics in Bacterial-Foraging optimization Algorithm., IEEE T SYST MAN CY A., vol. 39, no. 3, 670-679, 2009.
  22. Mishra, S., A Hybrid least square-Fuzzy Bacterial Foraging strategy for Harmonic Estimation., IEEE T EVOLUT COMPUT., vol. 9, no. 1, 61-73, 2005. July 2001. https://doi.org/10.1109/TEVC.2004.840144