Issue 1 (187), article 3

DOI: https://doi.org/10.15407/kvt187.01.030

Kibern. vyčisl. teh., 2017, Issue 1 (187), pp.30-49

Pavlov V.V., Doctor of Technics, Professor, Head of Intellectual Control Department
Shepetukha YU.M., PhD (technics), Senior Researcher, Senior Researcher of Intellectual Control Department
e-mail: yshep@meta.ua
Melnikov S.V., PhD (technics), Senior Researcher, Acting Head of Intellectual Control Department
e-mail: dep185@irtc.org.ua
Volkov A.E., Researcher of Intellectual Control Department
e-mail: alexvolk@ukr.net

International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine

INTELLIGENT CONTROL: APPROACHES, RESULTS AND PROSPECTS OF DEVELOPMENT

Introduction. Intelligent control systems are advanced computerized systems aimed at the modeling and analysis of intelligent tasks as well as the support of human activity in their solving. Therefore, consideration of both conceptual and applied issues of such systems’ development is an important and urgent scientific problem.

The purpose of the paper is to examine existing approaches, current state, important results and prospects for future development of such new scientific direction as intelligent control.

Methods. Artificial intelligence methods, man-machine theory, conflict resolution theory, theory of deterministic chaos, methods of decision support, methods of distributed control of non-linear applied processes.

Results. One may stress two main directions in the field of intelligent control where promising results have been achieved. The first one, related to the creation of intelligent infrastructure, includes development of methods and structures of distributed control as well as examination of non-linear applied processes in objects with variable properties. The second direction, attributed to the creation of intelligent agents, includes elaboration of methods, models and algorithms for real-time decisions related to the efficient control of dynamic objects.

Conclusion. Modern systems of intelligent control should integrate into a single unity three main components such as: traditional control methods, artificial intelligence theory and decision making approach. The main problem is the transformation of conceptual issues of intelligent systems’ creation into concrete technologies and algorithms of control in specific application domains.

Keywords: intelligent control, human-machine system, conflicts theory, non-linearity, uncertainty, net-centricity.

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REFERENCE

  1. Zilouchian A., Jamshidi M. Intelligent control systems using soft computing methodologies. Boca Raton: CRC Press, 2001. 492 p.
  2. Shtcherbatov I.A. Intelligent control of robot-technical systems in uncertainty conditions. Bulletin of Astrakhan State Technical University. 2010. №1. pp. 73–77 (in Russian).
  3. Antsaklis P.J. On intelligent control: report of the IEEE CSS task force on intelligent control. Technical report of the ISIS group №. ISIS 94-001. University of Notre Dame. 1994. 31 p.
  4. Albus J.S. On intelligence and its dimensions. Technical report of the ISIS (Interdisciplinary studies of intelligent systems) group №. ISIS 94-001. University of Notre Dame. 1994. P. 11–13.
  5. Antsaklis P.J. On autonomy and intelligence in control. Technical report of the ISIS group №. ISIS 94-001. University of Notre Dame. 1994. P. 14–18.
  6. Meystel A. On intelligent control, learning and hierarchies. Technical report of the ISIS group №. ISIS 94-001. University of Notre Dame. 1994. P. 14–18.
  7. Imam I.F., Kondratoff Y. Intelligent adaptive agents: a highlight of the AAAI-96 workshop. Artificial Intelligence. 1997. № 18(3). P. 75–80.
  8. Hess T.J., Rees L.P., Rakes T.R. Using autonomous software agents to create the next generation of decision support systems. Decision Sciences. 2000. Vol. 31. № 1. P. 1–31.
  9. Wooldridge M., Jennings N.R. Intelligent agents: theory and practice. The Knowledge Engineering Review. 1995. Vol. 10. № 2. P. 115–152.
  10. Intelligent infrastructure for the 21st century. VeriSign, Inc. Mountain View, CA,
    USA. 22 p. URL: http://complianceandprivacy.com/WhitePapers/VeriSign-Intelligent-Infrastructure-for-the-21syt-Century.pdf
  11. Vasilyev S.N. From classical automatic control problems to intelligent control. Theory and Systems of Control. 2001. № 1. pp. 5–22 (in Russian).
  12. XII International conference on intelligent systems and control “ISC-2009”. (Cambridge, 2009) URL: http://www.allconferences.com/conferences/2008/ 20081208150054.
  13. Pavlov V.V., Pavlova S.V. Intelligent control of complex non-linear dynamic systems: analytics of intelligence. Kiev: Nauk. dumka, 2015. 216 p. (in Russian).
  14. Nonaka I., G. von Krogh. Tacit knowledge and knowledge conversion: controversy and advancement in organizational knowledge creation theory. Organization Science. 2009. Vol. 20. № 3. P. 635–652.
  15. Pavlov V.V. Fundamentals of ergatic systems theory. Kiev: Nauk. dumka, 1975. 240 p. (in Russian).
  16. Pavlov V.V. Conflicts in engineering systems. Kiev: Vyshcha shkola, 1982. 184 p. (in Russian).
  17. Pavlov V.V. Synthesis of strategies in man-machine systems. Kiev: Vyshcha shkola, 1989. 162 p (in Russian).
  18. Bibichkov A., Pavlov V., Gricenko V., Gubanov S. “Anticon” — a step for the provision of navigation safety. Navigation. 1999. № 3. pp. 42–43 (in Russian).
  19. Method and device for computer networks of control of application processes’ high speed cycles: pat. 83118 Ukaine; reg. 08 Semtember 2006 (in Russian).

Recieved 02.10.2016