Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
SpringerLink
Log in

PSO optimal control of model-free adaptive control for PVC polymerization process

  • Research Article
  • Published:
International Journal of Automation and Computing Aims and scope Submit manuscript

Abstract

Polyvinyl chloride (PVC) polymerizing process is a typical complicated industrial process with the characteristics of large inertia, big time delay and nonlinearity. Firstly, for the general nonlinear and discrete time system, a design scheme of model-free adaptive (MFA) controller is given. Then, particle swarm optimization (PSO) algorithm is applied to optimizing and setting the key parameters for controller tuning. After that, the MFA controller is used to control the system of polymerizing temperature. Finally, simulation results are given to show that the MAC strategy based on PSO obtains a good controlling performance index.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Explore related subjects

Find the latest articles, discoveries, and news in related topics.

References

  1. Y. Li, L. Q. Yao, J. F. Li. Present status of PVC and development. China Chlor-Alkali, no. 3, pp. 1–3, 2006. (in Chinese)

    Google Scholar 

  2. G. Nemtoi, A. Onu, N. Aelenei, S. Dragan, C. Beldie. Thermal effects of some polymerisation and polycondensation reactions, polymeric ammonium quaternary salts. European Polymer Journal, vol. 36, no. 12, pp. 2679–2684, 2000.

    Article  Google Scholar 

  3. H. F. Ni, K. Debelak, D. Hunkeler. Fuzzy logic supervised ANN feedforward control for a batch polymerization reactor. In Proceedings of American Control Conference, IEEE, Seattle, WA, USA, pp. 1777–1781, 1995.

    Google Scholar 

  4. M. Huzmezan, G. A. Dumont, W. A. Gough, S. Kovac. Adaptive control of delayed integrating systems: A PVC batch reactor. IEEE Transactions on Control Systems Technology, vol. 11, no. 3, pp. 390–398, 2003.

    Article  Google Scholar 

  5. Q. L. Yang, H. P. Zhang, H. S. Liu. Intelligent control system of chloroethylene polyreaction process. Control and Instruments in Chemical Industry, vol. 34, no. 2, pp. 66–68, 2007. (in Chinese)

    Google Scholar 

  6. Z. Y. Zhou, G. B. Xu. Optimized PVC polymerization kettle temperature system design scheme. In Proceedings of International Conference on Electrical and Control Engineering, IEEE, Yichang, China, pp. 2418–2412, 2011.

    Google Scholar 

  7. S. Z. Gao, J. S. Wang, N. Zhao. Fault diagnosis method of polymerization kettle equipment based on rough sets and BP neural network. Mathematical Problems in Engineering, vol. 2013, Article number 768018, 2013.

    Google Scholar 

  8. Z. S. Hou, Z. G. Han. Robust modelless learning adaptive control of nonlinear systems. Control and Decision, vol. 10, no. 2, pp. 137–142, 1995. (in Chinese)

    MathSciNet  Google Scholar 

  9. K. K. Tan, S. N. Huang, T. H. Lee, F. M. Leu. Adaptivepredictive PI control of a class of SISO systems. In Proceedings of American Control Conference, IEEE, San Diego, CA, USA, pp. 3848–3852, 1999.

    Google Scholar 

  10. R. G. Lei. Tin thickness model-free adaptive control system for tinning line. Control Engineering China, vol. 12, no. 5, pp. 423–425, 2005. (in Chinese)

    Google Scholar 

  11. P. Ma, W. Li, G. W. Zheng, Y. G. Niu. The application of model free adaptive control. In Proceedings of the IMACS Multiconference on Computational Engineering in Systems Applications, IEEE, Beijing, China, pp. 393–396, 2006.

    Chapter  Google Scholar 

  12. J. Jiang, Y. X. Dai, Y. B. Zhang, R. Tang, W. L. Xiong. Multi-motor synchronization of multi-wire saw based on model-free adaptive control. Advanced Materials Research, vol. 69–70, pp. 660–664, 2009.

    Article  Google Scholar 

  13. J. Wang, C. Ji, L. L. Cao, Q. B. Jin. Design and realization of automatic control system for boiler based on model free adaptive control. In Proceedings of 2011 Chinese Control and Decision Conference, IEEE, Mianyang, China, pp. 1881–1886, 2011.

    Chapter  Google Scholar 

  14. W. Hu, J Tang. Study of model-free adaptive data-driven SMC algorithm. International Journal of Automation and Computing, vol. 13, no. 2, pp. 183–190, 2016.

    Article  Google Scholar 

  15. S. Z. Gao, J. S. Wang, X. W. Gao. Modeling and advanced control method of PVC polymerization process. Journal of Process Control, vol. 23, no. 5, pp. 664–681, 2013.

    Article  Google Scholar 

  16. S. Y. Zhang. Symmetric and similar structures of complex control systems. Control Theory & Applications, vol. 16, no. 2, pp. 231–237, 1994. (in Chinese)

    Google Scholar 

  17. F. Van den Bergh, A. P. Engelbreeht. A cooperative approach to particle swarm optimization. IEEE Transactions on Evolutionary Computation, vol. 8, no. 3, pp. 225–239, 2004.

    Article  Google Scholar 

  18. H. L. Shieh, C. C. Kuo, C. M. Chiang. Modified particle swarm optimization algorithm with simulated annealing behavior and its numerical verification. Applied Mathematics and Computation, vol. 218, no. 8, pp. 4365–4383, 2011.

    Article  MATH  Google Scholar 

  19. M. Pontani, B. A. Conway. Particle swarm optimization applied to impulsive orbital transfers. Acta Astronautica, vol. 74, pp. 141–155, 2012.

    Article  Google Scholar 

  20. S. Dhabal, P. Venkateswaran. Two-dimensional IIR filter design using simulated annealing based particle swarm optimization. Journal of Optimization, vol. 2014, Article number 239721, 2014.

    Google Scholar 

  21. S. Q. Chen, W. G. Xiao, L. J. Zeng, H. H. Wu. Optimal control of polymerization reactor. Control and Instruments in Chemical Industry, vol. 27, no. 4, pp. 10–12, 2000. (in Chinese)

    Google Scholar 

Download references

Acknowledgements

This work was supported by University of Science and Technology Liaoning, National Financial Security and System Equipment Engineering Research Center (No.USTLKFGJ201502).

Author information

Authors and Affiliations

  1. School of Electronic and Information Engineering, Shenyang University of Chemical Technology, Shenyang, 110142, China

    Shu-Zhi Gao, Xiao-Feng Wu, Liang-Liang Luan & Gui-Cheng Wang

  2. University of Science and Technology Liaoning, National Financial Security and System Equipment Engineering Research Center, Anshan, 114044, China

    Jie-Sheng Wang

Authors
  1. Shu-Zhi Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiao-Feng Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Liang-Liang Luan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jie-Sheng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Gui-Cheng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shu-Zhi Gao.

Additional information

Recommended by Associate Editor Yi Cao

Shu-Zhi Gao received the B. Sc. degree from Shenyang University of Chemical Technology, China in 1989, and received the M. Sc. degrees from Northeastern University, China in 2012. In 1989, she was a faculty member at Shenyang University of Chemical Technology. She is currently a professor and Ph.D. supervisor in Shenyang University of Chemical Technology. She has published about 30 refereed journal and conference papers.

Her research interests include feedback control system, modeling of complex industry process and intelligent control.

Xiao-Feng Wu received the B. Sc. degree in control science and engineering from Shenyang University of Chemical Technology, China in 2014. And now he is a Master student in control science and engineering at Shenyang University of Chemical Technology, China. He has published a journal when he is a graduate student.

His research interests include automatic control system and feedback control system.

Liang-Liang Luan received the B. Sc. degree in control science and engineering from Liaoning Shihua University, China in 2012. He was admitted as a graduate of Shenyang University of Chemical Technology from 2012.

His research interests include modeling of complex industry process and intelligent control.

Jie-Sheng Wang received the B. Sc. degree from Liaoning University of Science and Technology, China in 1999, and the M. Sc. degree from Dalian University of Technology, China in 2006. He is currently a professor and Ph.D. supervisor in Liaoning University of Science and Technology, China. He has published about 40 refereed journal and conference papers.

His research interests include modeling of complex industry process, intelligent control and computer integrated manufacturing.

Gui-Cheng Wang received the B. Sc. degree in 1993 and M. Sc. degrees in 1996 from Shenyang University of Chemical Technology, and the Ph. D. degree from Northeastern University, China in 2006. In 2010, his postdoctoral work is completed. Currently he is working as an associate professor and master supervisor in Shenyang University of Chemical Technology, China.

His research interests include computer control, computer simulation, intelligence control and intelligence information processing.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, SZ., Wu, XF., Luan, LL. et al. PSO optimal control of model-free adaptive control for PVC polymerization process. Int. J. Autom. Comput. 15, 482–491 (2018). https://doi.org/10.1007/s11633-016-0973-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11633-016-0973-7

Keywords

Search

Navigation