Skip to main content
SpringerLink
Log in

Acceleration and Increase of Reliability of the Algorithm for Numerical Optimization of the PID-Regulators for Automatic Control Systems

  • Conference paper
  • First Online:
Recent Research in Control Engineering and Decision Making (ICIT 2020)

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 337))

Abstract

Designing of regulators (controllers) is relevant in many areas of technology. The analytical calculation of the regulators does not justify itself, since it is possible only for objects that have the simplest models; there are relatively few such objects. For objects with a complex model, the method of numerical optimization is most effective. These methods can be used not only when the mathematical model of the object is known, but also in that case, the mathematical model of the object is not known. For this, a series of tests is performed with a real object, a given indicator of the quality of its work is evaluated, and the optimal regulator is calculated by the search procedure. Known search procedures are characterized by an extremely large required number of tests, some of which may prove fatal for the control object, so this method has not yet found wide application. This makes it extremely urgent to develop fast search algorithms that can soften the test mode and reduce their number. The paper offers several effective solutions to speed up the search algorithms, which gives new algorithms that are more effective than all known ones, including those that are embedded in specialized software for these purposes.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. van den Bosch, P.P.J., van der Klauw, A.C.: Modeling, Identification and Simulation of Dynamical Systems. CRC Press, Boca Raton (1994). ISBN 0-8493-9181-4

    MATH  Google Scholar 

  2. Ellah, A.R.A., Essai, M.H., Yahya, A.: Comparison of different backpropagation training algorithms using robust M-estimators performance functions. In: 2015 Tenth International Conference on Computer Engineering & Systems (ICCES), Cairo, pp. 384–388 (2015)

    Google Scholar 

  3. Forouzanfar, M., Dajani, H.R., Groza, V.Z., Bolic, M., Rajan, S.: Comparison of Feed-Forward Neural Network training algorithms for oscillometric blood pressure estimation. In: 4th International Workshop on Soft Computing Applications, Arad, pp. 119–123 (2010)

    Google Scholar 

  4. Wisesty, U.N., Adiwijaya, K.: Comparative study of conjugate gradient to optimize learning process of neural network for Intrusion Detection System (IDS). In: 2017 3rd International Conference on Science in Information Technology (ICSITech), Bandung, pp. 459–464 (2017)

    Google Scholar 

  5. Wu, Q.: A nonlinear conjugate gradient method without line search and its global convergence. In: 2011 International Conference on Computational and Information Sciences, Chengdu, China, pp. 1148–1152 (2011)

    Google Scholar 

  6. Trifonov, A.G.: Statement of the optimization problem and numerical methods for its solution (In Russian). https://hub.exponenta.ru/post/postanovka-zadachi-optimizatsii-i-chislennye-metody-ee-resheniya356

  7. Tang, K.S., Man, K.F., Kwong, S., He, Q.: Genetic algorithms and their applications. IEEE Sig. Process. Mag. 13(6), 22–37 (1996)

    Article  Google Scholar 

  8. Ji, P., Hu, X., Zhao, Q.: A new genetic algorithm for optimization. In: 2008 IEEE Conference on Cybernetics and Intelligent Systems, Chengdu, pp. 1092–1094 (2008)

    Google Scholar 

  9. Immanuel, S.D., Chakraborty, U.K.: Genetic algorithm: an approach on optimization. In: 2019 International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, pp. 701–708 (2019)

    Google Scholar 

  10. Zhmud, V., Liapidevskiy, A., Prokhorenko, E.: The design of the feedback systems by means of the modeling and optimization in the program VisSim 5.0/6. In: Proceedings of the IASTED International Conference on Modelling, Identification and Control. AsiaMIC 2010, 24–26 November 2010 Phuket, Thailand, pp. 27–32 (2010)

    Google Scholar 

  11. Zhmud, V., Yadrishnikov, O., Poloshchuk, A., Zavorin, A.: Modern key technologies in automatics: structures and numerical optimization of regulators. In: Proceedings - 2012 7th International Forum on Strategic Technology, IFOST 2012, Tomsk, Russia (2012)

    Google Scholar 

  12. Zhmud, V., Yadrishnikov, O.: Numerical optimization of PID-regulators using the improper moving detector in cost function. In: Proceedings of the 8-th International Forum on Strategic Technology, IFOST-2013, Ulaanbaatar, Mongolia, 28 June–1 July, vol. II, pp. 265–270 (2013)

    Google Scholar 

  13. https://help.simintech.ru/#o_simintech/o_simintech.html

Download references

Author information

Authors and Affiliations

  1. Novosibirsk State Technical University, Karl Marx Ave. 20, 630073, Novosibirsk, Russia

    Vadim Zhmud

  2. Faculty of Mechanical Engineering, Technical University of Sofia, Bul. St. Kliment Ohridski, 8, 1756, Studentski Complex, Sofia, Bulgaria

    Lubomir Dimitrov

  3. Technical University of Liberec, Studentská 1402/2, 461 17, Liberec, Czech Republic

    Jaroslav Nosek

Authors
  1. Vadim Zhmud
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lubomir Dimitrov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jaroslav Nosek
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vadim Zhmud .

Editor information

Editors and Affiliations

  1. Yury Gagarin State Technical University of Saratov, Saratov, Russia

    Olga Dolinina

  2. ITMO University, Saint Petersburg, Russia

    Igor Bessmertny

  3. Yury Gagarin State Technical University of Saratov, Saratov, Russia

    Alexander Brovko

  4. University of Texas at El Paso, El Paso, USA

    Vladik Kreinovich

  5. Yury Gagarin State Technical University of Saratov, Saratov, Russia

    Vitaly Pechenkin

  6. Yury Gagarin State Technical University of Saratov, Saratov, Russia

    Alexey Lvov

  7. Novosibirsk State Technical University, Novosibirsk, Russia

    Vadim Zhmud

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhmud, V., Dimitrov, L., Nosek, J. (2021). Acceleration and Increase of Reliability of the Algorithm for Numerical Optimization of the PID-Regulators for Automatic Control Systems. In: Dolinina, O., et al. Recent Research in Control Engineering and Decision Making. ICIT 2020. Studies in Systems, Decision and Control, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-030-65283-8_3

Download citation

Publish with us

Policies and ethics

Search

Navigation