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Issue 1 (195), article 1

DOI:https://doi.org/10.15407/kvt195.01.005

Kibern. vyčisl. teh., 2019, Issue 1 (195), pp.

Grytsenko V.I., Corresponding Member of NAS of Ukraine,
Director of International Research and Training
Center for Information Technologies and Systems
of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine
e-mail: vig@irtc.org.ua

Volkov A.E., Acting Head of Department,
Intelligent Control Department,
e-mail: alexvolk@ukr.net

Komar N.N., Researcher,
Intelligent Control Department,
e-mail: nickkomar08@gmail.com

Shepetukha Yu.M., PhD (Engineering)
Leading Researcher,
Intelligent Control Department,
e-mail: dep185@irtc.org

Voloshenyuk D.A., Researcher,
Intelligent Control Department,
e-mail: dep185@irtc.org

International Research and Training Center for Information Technologies
and Systems of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine,
Acad. Glushkov av., 40, Kiev, 03187, Ukraine

INTEGRAL-ADAPTIVE AUTOPILOT AS A MEANS OF INTELLECTUALIZING A MODERN UNMANNED AERIAL VEHICLE

Introduction. At present unmanned aerial vehicles (UAVs) are successfully used in various industries in performing scientific and engineering, economical, military and a number of other missions. Effectiveness of their functioning is mainly determined by an onboard suit of hardware and software of a UAV’s control system. The process of the existing autopilot systems enhancement is intended to broaden the range of UAV’s tasks without direct human involvement and introduce additional smart functions into autopilot operation.

Purpose. The aim of research is to study the modern algorithms used in autopilots of unmanned aerial vehicles and formulation of the problem of development and usage of new intellectual methods for automatic control systems.

Results. The approach considered in the article is based on the theory of high-precision remote control of dynamic objects and on the complex interaction of methods of theory of invariance, adaptive control and intellectualization of processes of UAV control.

One of the features of the proposed method of intellectual control for unmanned aerial vehicle autopilot is the procedure of transforming a multi-dimensional system into an aggregate of virtual autonomous processes, for each of which the control algorithm is easily generated by an autonomous subsystem. Coming up next is the procedure of coordination of actions of all the autonomous systems into single functioning complex. This provides an opportunity to improved precision and sustainability of control.

Conclusion. Using the method described in the article allows creating integral and adaptive autopilots to perform complicated spatial maneuvering an unmanned aerial vehicle being based on usage of full non-linear models without simplifications and linearization.

Keywords: unmanned aerial vehicle, control system, virtual control, adaptation invariance.

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REFERENCES

1 Fahlstrom P., Gleason T. Introduction to UAV systems. Hoboken: Wiley, 2012. 4th ed. 308 p. https://doi.org/10.1002/9781118396780

2 Moiseyev V.S. Applied theory of unmanned aerial vehicles control. Kazan: GBU Republican centre for monitoring education quality, 2013.p. 768. (in Russian).

3 Beard R.W., McLain T.W. Small Unmanned Aircraft: Theory and Practice. Princeton: Princeton Univ. Press, 2012. 320 p. https://doi.org/10.1515/9781400840601

4 Chao H., Cao Y., and Chen Y.Q. Autopilots for small unmanned aerial vehicles: a survey. International Journal of Control, Automation, and Systems, 2010, vol. 8, N 1. P. 36-44. https://doi.org/10.1007/s12555-010-0105-z

5 Feng G. A survey on analysis and design of model-based fuzzy control systems. IEEE Transactions on Fuzzy Systems, 2006, vol. 14, N 5. P. 676 – 697. https://doi.org/10.1109/TFUZZ.2006.883415

6 Shilov K.Ye. Development of unmanned air vehicle automatic control system of a rotorcraft. Works of MFTI, 2014. N 4 . P. 139-152. (in Russian).

7 Calise A., Rysdyk R. Nonlinear Adaptive Flight Control Using Neural Networks. Control Systems Magazine, 1998, vol. 18, N. 6. P. 14-25. https://doi.org/10.1109/37.736008

8 Johnson E.N., Kannan S.K. Adaptive Flight Control for an Autonomous Unmanned Helicopter. AIAA Guidance, Navigation, and Control Conference and Exhibit. Monterey, California, August, 2002. https://doi.org/10.2514/6.2002-4439

9 Lopez J., Dormido R., Gomez J.P., Dormido S., Diaz J.M. Comparison of H-infinity with QFT applied to an Altitude Command Tracker for an UAV. Proc. of the European Control Conference (2 – 5th of July, 2007, Kos, Greece) Kos, Greece, 2007. P. 46-54. https://doi.org/10.23919/ECC.2007.7068482

10 Lopez J., Dormido R., Dormido S., Gomez J.P. A Robust Controller for an UAV Flight Control System. The Scientific World Journal. 2015. vol. 2015. P. 15-26. https://doi.org/10.1155/2015/403236

11 Ross T.J. Fuzzy Logic with Engineering Applications, 2nd Edition. NY: Wiley, 2004. 228 p.

12 Kumon M., Udo Y., Michihira H., Nagata M., Mizumoto I., Iwai Z. Autopilot system for kiteplane. IEEE/ASME Transactions on Mechatronics. 2006. vol. 11. N 5. P. 615-624. https://doi.org/10.1109/TMECH.2006.882994

13 Albus J.S. On intelligence and its dimensions. Technical report of the ISIS (Interdisciplinary studies of intelligent systems) group N. ISIS 94-001. University of Notre Dame, 1994. P. 11-13.

14 Antsaklis P.J. On autonomy and intelligence in control. Technical report of the ISIS (Interdisciplinary studies of intelligent systems) group N. ISIS 94-001. University of Notre Dame, 1994. P. 14-18.

15 Grytsenko V.I., Volkov O.E., Komar M.M., Bogachuk Yu.P. Intellectualization of the modern automatic control systems for unmanned aerial vehicles. Kibernetika i vycislitelnaa tehnika. 2018. N 1 (191). P. 45-59. (in Ukrainian) https://doi.org/10.15407/kvt191.01.045

16 Pavlov V.V., Pavlova S.V. Intellectual control of complex non-linear dynamic systems. Kiev: Naukova dumka. 2015. 216 p. (in Russian).

17 Kharchenko V.P., Chepizhenko V.I., Tounik A.A., Pavlova S.V. Unmanned aerial vehicles avionics. Kiev: TOV Abris-print, 2012. 464 p. (in Ukrainian).

18 Bodner V.A. Air vehicle control systems. Moscow: Mashinostroyeniye, 1973. 501 p. (in Russian).

Received 19.11.2018

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Issue 1 (191), article 3

DOI:https://doi.org/10.15407/kvt191.01.045

Kibern. vyčisl. teh., 2018, Issue 1 (191), pp.

Grytsenko V.I., Corresponding Member of NAS of Ukraine,
Director of International Research and Training
Center for Information Technologies and Systems
of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine
e-mail: vig@irtc.org.ua
Volkov О.Y., Senior Researcher,
Intellectual Control Department
e-mail: alexvolk@ukr.net
Komar M.M., Researcher,
Intellectual Control Department
e-mail: nickkomar08@gmail.com
Bogachuk Y.P., PhD (Engineering), Senior Researcher,
Intellectual Control Department
e-mail: dep185@irtc.org.ua
International Research and Training Center for Information
Technologies and Systems of the National Academy
of Sciences of Ukraine and Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., 03187, Kiev, Ukraine

INTELLECTUALIZATION OF MODERN SYSTEMS OF AUTOMATIC CONTROL OF UNMANNED AERIAL VEHICLES

Introduction. The article discusses the actual questions of the need of creation of modern systems of automatic control of unmanned aerial vehicle (UAV) and describes new methods of its intellectualization. Today’s development of information technology requires accelerated development of the theory of intellectual control and the theory of systemic information technology. New technologies of intellectual control are extremely important for solving the problems of modern unmanned aviation.
The purpose of the article is to solve the issues of the development of the control system of UAV and to provide a number of measures aimed to ensuring its intellectualization. The approach considered in the article is based on the theory of high-precision remote control of dynamic objects and on the complex interaction of methods of theory of invariance, adaptive control and intellectualization of processes of UAV control.
Results. The development and implementation of control algorithms using functional program modules written in modern high-level programming languages in the computer environment based on microprocessors with a computing power sufficient to implement these algorithms in the form of a unified hardware and software complex of the integrated avionics.
The expansion of the range of functional capabilities of UAV control system that is offered to supplement the developed channels and algorithms of autopilot by the methods of intellectualization.
Conclusions. It is shown that combining the developed control laws for UAV autopilot into a unified hardware and software complex of integrated avionics and supplementing them with the proposed components of intellectualization will create a synergy effect and ensure the effectiveness and sustainability of the process of controlling the motion of the UAV.

Keywords: unmanned aerial vehicle, control system, invariance, intellectualization,

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REFERENCES

  1. Krasil’shchikovM.N., SerebryakovG.G.Modern information technologies in the tasks of navigation and guidance of unmanned maneuverable aircrafts. Moscow: FIZMATLIT, 2009. 556 p. (in Russian).
  2. Kharchenko V.P., Chepizhenko V.I., Tunik A.А., Pavlova S.V. Avionic-sofunmannedaerialvehicles. Kyiv: Abris-Print, 2012. 464 p. (in Ukrainian)
  3. Fedosov E.A., Bobronnikov V.T., Kukhtenko V.I. Dynamic design of control systems for automatic maneuverable aircrafts. Moscow: Mashinostroyeniye, 1997. 336 p. (In Russian).
  4. Pavlova S., Komar M. The Invariant Adaptation of the Aircraft Control System in Emergency Situation During the Flight. ProceedingoftheNationalAviationUniversity. 2016. № 4(69). P. 28–33.
  5. Fahlstrom P., Gleason T. Introduction to UAV systems. Hoboken: Wiley, 2012. 4th ed. 308 p.
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  7. Austin R. Unmannedaircraftsystems. UAVsdesign, developmentanddeployment. JohnWiley&Sons, 2010. 372 p.
  8. Randal W. Beard, Timothy W. McLaine Small unmanned aerial vehicles: theory and practice. Moscow: TEKHNOSFERA, 2015. 312 c.
  9. AlyoshinB.S.Orientationandnavigationofmobileobjects: moderninformationtechnologies. Moscow: FIZMATLIT, 2006. 424 p. (In Russian).
  10. Volkov A.E., Pavlova S.V. Modelingoftheinvariantmethodforresolvingthedynamic-conflictsofaircraft. Cyberneticsandsystemsanalysis. 2017. № 53 (4). P. 105–112 (In Russian).
  11. Voloshenyuk D.A., Pavlova S.V. Managementofaircraftlandinginconditionsofincreasing-airtraffic. Controlsystemsandmachines. 2017 № 5. P. 62–74 (In Russian).

Received 27.12.2017

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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.
https://doi.org/10.1201/9781420058147

2 Shtcherbatov I.A. Intelligent control of robot-technical systems in uncertainty conditions. Bulletin of Astrakhan State Technical University. 2010. No1. 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 No. 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 No. 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 No. 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 No. 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. No 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. No 1. P. 1–31.
https://doi.org/10.1111/j.1540-5915.2000.tb00922.x

9 Wooldridge M., Jennings N.R. Intelligent agents: theory and practice. The Knowledge Engineering Review. 1995. Vol. 10. No 2. P. 115–152.
https://doi.org/10.1017/S0269888900008122

10 Intelligent infrastructure for the 21st century. VeriSign, Inc. Mountain View, CA,

11 USA. 22 p. URL: http://complianceandprivacy.com/WhitePapers/VeriSign-Intelligent-Infrastructure-for-the-21syt-Century.pdf

12 Vasilyev S.N. From classical automatic control problems to intelligent control. Theory and Systems of Control. 2001. No 1. pp. 5–22 (in Russian).

13 XII International conference on intelligent systems and control “ISC-2009”. (Cambridge, 2009) URL: http://www.allconferences.com/conferences/2008/ 20081208150054.

14 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).

15 Nonaka I., G. von Krogh. Tacit knowledge and knowledge conversion: controversy and advancement in organizational knowledge creation theory. Organization Science. 2009. Vol. 20. No 3. P. 635–652.
https://doi.org/10.1287/orsc.1080.0412

16 Pavlov V.V. Fundamentals of ergatic systems theory. Kiev: Nauk. dumka, 1975. 240 p. (in Russian).

17 Pavlov V.V. Conflicts in engineering systems. Kiev: Vyshcha shkola, 1982. 184 p. (in Russian).

18 Pavlov V.V. Synthesis of strategies in man-machine systems. Kiev: Vyshcha shkola, 1989. 162 p (in Russian).

19 Bibichkov A., Pavlov V., Gricenko V., Gubanov S. “Anticon” — a step for the provision of navigation safety. Navigation. 1999. No 3. pp. 42–43 (in Russian).

20 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

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Issue 186, article 5

DOI:https://doi.org/10.15407/kvt186.04.046

KVT, 2016, Issue 186, pp.46-56

UDC 681.518

NETWORK-CENTRIC CONTROL TECHNOLOGY OF DATA TRANSFER BY NETWORK COMMUNICATIONS

Melnikov S.V., Volkov A.E., Komar N.N., Voloshenyuk D.A.

International Research and Training Center for Information Technologies and Systems, Kyiv, Ukraine

dep185@irtc.org.ua , alexvolk@ukr.net , komko08@ukr.net , p-h-o-e-n-i-x@ukr.net

Introduction. The problem of increasing network performance is very relevant. In practice, the actual speed of data transmission / receiving is significantly lower than the bit rate supported by used network technology. The actual wireless network bandwidth depends on the used technology, the number of subscribers in the network, length and quality of communication channels, electromagnetic interference, weather, network equipment, protocols and many other factors.

The purpose. The project is based on applied research in the field of high-speed cycles control systems for net-centric dynamic application processes with spatially-distributed interrelated functional components. Thus it provides functional and temporal combination of internal resources of net-centric distributed control systems with objects and technological processes on the basis of shared use of dynamics models working in an accelerated time scale into a single space-time net-centric complex.

Results. To solve the problem of determining the quality of the data transfer process in order to further control and manage this process, a method which is based on software that works with any standardized computing environment was developed. This method detects and evaluates the operating parameters of the wired Internet network before, during and after transmission of the information data packets provides analytical (numerical values of time delay of packet transmission, the percentage of lost data, signal quality, transmission speed and receive speed) and graphic parameters to control information transmission routes. This paper provides the results of computer simulation which are represent the network connection quality.

Conclusion. Development a method for determining the quality of information data transmission via a wireless connection, also as a creating programs for protection against unauthorized network access — are a perspective research objectives. Results of simulations confirm the appropriateness of using the given method of data transfer control in the terrestrial wired data transmission systems and the need to develop such technology for wireless connection.

Keywords: network-centric; control technology; communication; computer modeling; virtual model.

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Reference

  1. A.A. Mizin Transmission of information via circuit-switched communications networks. M.: Communications, 1977, 328 p.
  2. S.V. Pavlova, Y.P. Bogachuk, S.V. Melnikov Simulation technology of distributed network of aircraft control. Kibernetika i vyčislitelʹnaâ tehnika, 2011, Vol. 163, pp. 45–53.
  3. Method of control of the route and determine the quality of the transfer of information data through a wired Internet network. Patent of Ukraine №04108, IPC (2013) G06N 7/00, stated 15/05/2014, Published 07/16/2014.
  4. V.P. Kharchenko, S.M. Kredentsar Networks and databases. NAU, Kiev, 2013, 328 p.
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  6. S.M. Pauk Aeronautical Telecommunication Networks. M.: Transport, 1986, 271 p.

Received 28.11.2016

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ISSUE 180, article 5

DOI:https://doi.org/10.15407/kvt180.02.045

Kibern. vyčisl. teh., 2015, Issue 179, pp 45-65.

Pavlov Vadim V., Dr (Engineering), Prof., Head of the Department of Intellectual Control of International Research and Training Center for Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, av. Acad. Glushkova, 40, Kiev, 03187, Ukraine, e-mail: dep185@irtc.org.ua

Volkov Aleksandr E., PG (Postgraduate) of the Department of Intellectual Control of International Research and Training Center for Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, av. Acad. Glushkova, 40, Kiev, 03187, Ukraine, e-mail: alexvolk@ukr.net

Voloshenyuk Dmitrii A., PG (Postgraduate) of the Department of Intellectual Control of International Research and Training Center for Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, av. Acad. Glushkova, 40, Kiev, 03187, Ukraine, e-mail: P-h-o-e-n-i-x@ukr.net

INVARIANT NET-CENTRIC CONTROL SYSTEM FOR CONFLICT AVOIDANCE OF AIRCRAFTS IN THE LANDING PHASE

Introduction. The question of the need to create a control system of conflict situations between the aircrafts in the landing phase is discusses.

The purpose of this research is to create a method and system of conflict resolution between the aircrafts on the route of flight, takeoff and landing phases with the condition to provide a high and guaranteed level of flight safety. The approach considered in the article will be based on the principles of using the network-centric technologies and the theory of invariance.

Results. The expected result of this work is the creation of a new universal control system of conflict situations between the aircrafts based on network-centric technologies and principles of the theory of invariance, which will meet all the requirements of modern air traffic management (ATM) to provide a guaranteed level of safety.

Conclusion. It is shown that a new approach to the problem of creating a control system of conflict situations between the aircrafts based on research in the field of differential games and the theory of invariance is effective.

Keywords: net-centric system, flight safety, invariance, conflict situations, differential games, free flight.

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Received 23.02.2015