Skip to main content
SpringerLink
Log in
Book cover

International Conference on Artificial Intelligence and Soft Computing

ICAISC 2015: Artificial Intelligence and Soft Computing pp 247–260Cite as

Aspects of Structure and Parameters Selection of Control Systems Using Selected Multi-Population Algorithms

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9120))

Abstract

In this paper a new approach for automatic design of control systems is presented. It is based on multi-population algorithms and allows to select not only parameters of control systems, but also its structure. Proposed approach was tested on a problem of stabilization of double spring-mass-damp object.

This is a preview of subscription content, 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   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bartczuk, Ł., Dziwiński, P., Starczewski, J.T.: New method for generation type-2 fuzzy partition for FDT. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part I. LNCS(LNAI), vol. 6113, pp. 275–280. Springer, Heidelberg (2010)

    Google Scholar 

  2. Bartczuk, Ł., Przybył, A., Koprinkova-Hristova, P.: New method for nonlinear fuzzy correction modelling of dynamic objects. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2014, Part I. LNCS(LNAI), vol. 8467, pp. 169–180. Springer, Heidelberg (2014)

    Google Scholar 

  3. Bartczuk, Ł., Dziwiński, P., Starczewski, J.T.: A new method for dealing with unbalanced linguistic term set. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part I. LNCS, vol. 7267, pp. 207–212. Springer, Heidelberg (2012)

    Google Scholar 

  4. Borovska, P., Lazarova, M.: Migration policies for island genetic models on multicomputer platform. In: Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, pp. 143–148 (2007)

    Google Scholar 

  5. Cantu-Paz, E.: Topologies, migration rates, and multi-population parallel genetic algorithms (1999)

    Google Scholar 

  6. Cpałka, K., Łapa, K., Przybył, A., Zalasin ́ski, M.: A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects. Neurocomputing 135, 203–217 (2014)

    Google Scholar 

  7. Cpałka, K.: On evolutionary designing and learning of flexible neuro-fuzzy structures for nonlinear classification. Nonlinear Analysis Series A: Theory, Methods and Applications 71, 1659–1672 (2009)

    Google Scholar 

  8. Cpałka, K., Rebrova, O., Nowicki, R., Rutkowski, L.: On design of flexible neuro-fuzzy systems for nonlinear modelling. Int. Journal of General Systems 42(6), 706–720 (2013)

    Google Scholar 

  9. Cpałka, K., Rutkowski, L.: Flexible Takagi-Sugeno Fuzzy Systems. In: Proceedings of the International Joint Conference on Neural Networks 2005, Montreal, pp. 1764–1769 (2005)

    Google Scholar 

  10. Cpałka, K., Rutkowski, L.: A New Method for Designing and Reduction of Neuro-fuzzy Systems. In: Proceedings of the 2006 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence, WCCI 2006), Vancouver, BC, Canada (2006), pp. 8510–8516 (2006)

    Google Scholar 

  11. Cpałka, K., Zalasiński, M.: On-line signature verification using vertical signature partitioning. Expert Systems with Applications 41, 4170–4180 (2014)

    Google Scholar 

  12. Cpałka, K., Zalasiński, M., Rutkowski, L.: New method for the on-line signature verification based on horizontal partitioning. Pattern Recognition 47, 2652–2661 (2014)

    Google Scholar 

  13. Dziwiński, P., Bartczuk, Ł., Starczewski, J.T.: Fully controllable ant colony system for text data clustering. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) SIDE 2012 and EC 2012. LNCS, vol. 7269, pp. 199–205. Springer, Heidelberg (2012)

    Google Scholar 

  14. Dziwiński, P., Starczewski, J.T., Bartczuk, Ł.: New linguistic hedges in construction of interval type-2 fls. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part II. LNCS(LNAI), vol. 6114, pp. 445–450. Springer, Heidelberg (2010)

    Google Scholar 

  15. Dziwiński, P., Bartczuk, Ł., Przybył, A., Avedyan, E.D.: A New Algorithm for Identification of Significant Operating Points Using Swarm Intelligence. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2014, Part II. LNCS(LNAI), vol. 8468, pp. 349–362. Springer, Heidelberg (2014)

    Google Scholar 

  16. El-Abd, M.: On the hybridization on the artificial bee colony and particle swarm optimization algorithms. Journal of Artificial Intelligence and Soft Computing Research 2(2), 147–155 (2012)

    MathSciNet  Google Scholar 

  17. Fogel, D.B.: Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, 3rd edn. IEEE Press, Piscataway (2006)

    Google Scholar 

  18. Gabryel, M., Cpałka, K., Rutkowski, L.: Evolutionary strategies for learning of neuro-fuzzy systems. In: I Workshop on Genetic Fuzzy Systems, Granada, pp. 119–123 (2005)

    Google Scholar 

  19. Gabryel, M., Woźniak, M., K. Nowicki, R.: Creating Learning Sets for Control Systems Using an Evolutionary Method. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) SIDE 2012 and EC 2012. LNCS, vol. 7269, pp. 206–213. Springer, Heidelberg (2012)

    Google Scholar 

  20. Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proc. IEEE Int’l Conf. on Neural Networks, vol. IV, pp. 1942–1948 (1995)

    Google Scholar 

  21. Korytkowski, M., Rutkowski, L., Scherer, R.: From ensemble of fuzzy classifiers to single fuzzy rule base classifier. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2008. LNCS (LNAI), vol. 5097, pp. 265–272. Springer, Heidelberg (2008)

    Google Scholar 

  22. Leva, A., Papadopoulos, A.V.: Tuning of event-based industrial controllers with simple stability guarantees. Journal of Process Control 23, 1251–1260 (2013)

    Google Scholar 

  23. Li, W.: Design of PID Controller Based on an Expert System. International Journal of Computer, Consumer and Control (IJ3C) 3(1), 31–40 (2014)

    Google Scholar 

  24. Lobato, F.S., Steffen Jr., V.: A new multi-objective optimization algorithm based on differential evolution and neighborhood exploring evolution strategy. Journal of Artificial Intelligence and Soft Computing Research 1(4), 259–267 (2011)

    Google Scholar 

  25. Lobato, F.S., Steffen Jr., V., Silva Neto, A.J.: Solution of singular optimal control problems using the improved differential evolution algorithm. Journal of Artificial Intelligence and Soft Computing Research 1(3), 195–206 (2011)

    Google Scholar 

  26. Łapa, K., Przybył, A., Cpałka, K.: A new approach to designing interpretable models of dynamic systems. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part II. LNCS(LNAI), vol. 7895, pp. 523–534. Springer, Heidelberg (2013)

    Google Scholar 

  27. Łapa, K., Zalasiński, M., Cpałka, K.: A new method for designing and complexity reduction of neuro-fuzzy systems for nonlinear modelling. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part I. LNCS(LNAI), vol. 7894, pp. 329–344. Springer, Heidelberg (2013)

    Google Scholar 

  28. Malhotra, R., Sodh, R.: Boiler Flow Control Using PID and Fuzzy Logic Controller. IJCSET 1(6), 315–331 (2011)

    Google Scholar 

  29. Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer (1999)

    Google Scholar 

  30. Niu, B., Zhu, Y., He, X., Wu, H.: MCPSO: A multi-swarm cooperative particle swarm optimizer. Applied Mathematics and Computation 185(2,15), 1050–1062 (2007)

    Google Scholar 

  31. Osaba, E., Diaz, F., Onieva, E.: Golden ball: a novel metaheuristic to solve combinatorial optimization problems based on soccer concepts. Applied Intelligence 41(1), 145–166 (2014)

    Google Scholar 

  32. Perng, J.-W., Chen, G.-Y., Hsieh, S.-C.: Optimal PID Controller Design Based on PSO-RBFNN for Wind Turbine Systems. Energies 7, 191–209 (2014)

    Google Scholar 

  33. Prampero, P.S., Attux, R.: Magnetic particle swarm optimization. Journal of Artificial Intelligence and Soft Computing Research 2(1), 59–72 (2012)

    Google Scholar 

  34. Przybył, A., Cpałka, K.: A new method to construct of interpretable models of dynamic systems. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part II. LNCS, vol. 7268, pp. 697–705. Springer, Heidelberg (2012)

    Google Scholar 

  35. Przybył, A., Er, M.J.: The idea for the integration of neuro-fuzzy hardware emulators with real-time network. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2014, Part I. LNCS(LNAI), vol. 8467, pp. 279–294. Springer, Heidelberg (2014)

    Google Scholar 

  36. Przybył, A., Jelonkiewicz, J.: Genetic algorithm for observer parameters tuning in sensorless induction motor drive. Neural Networks and Soft Computing, pp. 376–381 (2003)

    Google Scholar 

  37. Przybył, A., Smoląg, J., Kimla, P.: Distributed control system based on real time ethernet for computer numerical controlled machine tool. Przegląd Elektrotechniczny 86(2), 342–346 (2010) (in Polish)

    Google Scholar 

  38. Rasoanarivo, I., Brechet, S., Battiston, A., Nahid-Mobarakeh, B.: Behavioral Analysis of a Boost Converter with High Performance Source Filter and a Fractional-Order PID Controller. In: IEEE Industry Applications Society Annual Meeting (IAS), pp. 1–6 (2012)

    Google Scholar 

  39. Rini, D.P., Shamsuddin, S.M., Yuhaniz, S.S.: Particle Swarm Optimization: Technique, System and Challenges. International Journal of Computer Applications (0975-8887) 14(1), 19–27 (2011)

    Google Scholar 

  40. Rutkowski, L.: Sequential estimates of probability densities by orthogonal series and their application in pattern-classification. IEEE Trans. Systems Man and Cybernetics 10(2), 918–920 (1980)

    MathSciNet  Google Scholar 

  41. Rutkowski, L.: Multiple Fourier-series procedures for extraction of nonlinear regressions from noisy data. IEEE Trans. Signal Processing 41(10), 3062–3065 (1993)

    Google Scholar 

  42. Rutkowski, L.: Computational Intelligence. Springer (2008)

    Google Scholar 

  43. Rutkowski, L., Cpałka, K.: A neuro-fuzzy controller with a compromise fuzzy reasoning. Control and Cybernetics 31(2), 297–308 (2002)

    Google Scholar 

  44. Rutkowski, L., Cpałka, K.: Compromise approach to neuro-fuzzy systems. In: Sincak, P., Vascak, J., Kvasnicka, V., Pospichal, J. (eds.) Intelligent Technologies - Theory and Applications, vol. 76, pp. 85–90. IOS Press (2002)

    Google Scholar 

  45. Rutkowski, L., Cpałka, K.: Neuro-fuzzy systems derived from quasi-triangular norms. In: Proceedings of the IEEE International Conference on Fuzzy Systems, Budapest, July 26-29, vol. 2, pp. 1031–1036 (2004)

    Google Scholar 

  46. Rutkowski, L., Przybył, A., Cpałka, K., Er, M.J.: Online speed profile generation for industrial machine tool based on neuro-fuzzy approach. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part II. LNCS(LNAI), vol. 6114, pp. 645–650. Springer, Heidelberg (2010)

    Google Scholar 

  47. Skolicki, Z., De Jong, K.: The influence of migration sizes and intervals on island models. In: GECCO 2005: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, pp. 1295–1302 (2005)

    Google Scholar 

  48. Starczewski, J.T., Bartczuk, Ł., Dziwiński, P., Marvuglia, A.: Learning methods for type-2 FLS based on FCM. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part I. LNCS(LNAI), vol. 6113, pp. 224–231. Springer, Heidelberg (2010)

    Google Scholar 

  49. Szczypta, J., Łapa, K., Shao, Z.: Aspects of the Selection of the Structure and Parameters of Controllers Using Selected Population Based Algorithms. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2014, Part I. LNCS(LNAI), vol. 8467, pp. 440–454. Springer, Heidelberg (2014)

    Google Scholar 

  50. Szczypta, J., Przybył, A., Cpałka, K.: Some aspects of evolutionary designing optimal controllers. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part II. LNCS(LNAI), vol. 7895, pp. 91–100. Springer, Heidelberg (2013)

    Google Scholar 

  51. Szczypta, J., Przybył, A., Wang, L.: Evolutionary approach with multiple quality criteria for controller design. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2014, Part I. LNCS(LNAI), vol. 8467, pp. 455–467. Springer, Heidelberg (2014)

    Google Scholar 

  52. Theodoridis, D.C., Boutalis, Y.S., Christodoulou, M.A.: Robustifying analysis of the direct adaptive control of unknown multivariable nonlinear systems based on a new neuro-fuzzy method. Journal of Artificial Intelligence and Soft Computing Research 1(1), 59–79 (2011)

    Google Scholar 

  53. Tran, V.N., Brdys, M.A.: Optimizing control by robustly feasible model predictive control and application to drinking water distribution systems. Journal of Artificial Intelligence and Soft Computing Research 1(1), 43–57 (2011)

    Google Scholar 

  54. Zalasiński, M., Łapa, K., Cpałka, K.: New Algorithm for Evolutionary Selection of the Dynamic Signature Global Features. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part II. LNCS(LNAI), vol. 7895, pp. 113–121. Springer, Heidelberg (2013)

    Google Scholar 

  55. Zalasiński, M., Cpałka, K.: Novel algorithm for the on-line signature verification. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part II. LNCS, vol. 7268, pp. 362–367. Springer, Heidelberg (2012)

    Google Scholar 

  56. Zalasiński, M., Cpałka, K.: New approach for the on-line signature verification based on method of horizontal partitioning. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part II. LNCS(LNAI), vol. 7895, pp. 342–350. Springer, Heidelberg (2013)

    Google Scholar 

  57. Zalasiński, M., Cpałka, K.: Novel Algorithm for the On-Line Signature Verification Using Selected Discretization Points Groups. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013, Part I. LNCS(LNAI), vol. 7894, pp. 493–502. Springer, Heidelberg (2013)

    Google Scholar 

  58. Zalasiński, M., Cpałka, K., Er, M.J.: New Method for Dynamic Signature Verification Using Hybrid Partitioning. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2014, Part II. LNCS(LNAI), vol. 8468, pp. 216–230. Springer, Heidelberg (2014)

    Google Scholar 

  59. Zalasiński, M., Cpałka, K., Hayashi, Y.: New Method for Dynamic Signature Verification Based on Global Features. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2014, Part II. LNCS(LNAI), vol. 8468, pp. 231–245. Springer, Heidelberg (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Computational Intelligence, Czȩstochowa University of Technology, Czȩstochowa, Poland

    Krystian Łapa & Jacek Szczypta

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Rajasekar Venkatesan

Authors
  1. Krystian Łapa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jacek Szczypta
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rajasekar Venkatesan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Krystian Łapa .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Czestochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Czestochova Univ of Technology, Częstochova, Poland

    Rafal Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. Louisville, Kentucky, USA

    Jacek M. Zurada

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Łapa, K., Szczypta, J., Venkatesan, R. (2015). Aspects of Structure and Parameters Selection of Control Systems Using Selected Multi-Population Algorithms. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9120. Springer, Cham. https://doi.org/10.1007/978-3-319-19369-4_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-19369-4_23

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19368-7

  • Online ISBN: 978-3-319-19369-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation