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This article is devoted to the adaptive cyclic control of an industrial robot manipulator
on the example of moving objects with a positional trajectory. The specific features of applying the
principle of adaptive cyclic control to industrial robots are also presented. The kinematic scheme
describing the movement of the robot working body with the adaptive cycle control system and the
transition states of the working body based on limited positions in space are presented, the sequence of
movement of the manipulator links and the selection of information about the actions at individual levels
of mobility, control in the case of a variable sequence of links by positional coordinates the formation
of programs was considered. During the control process, a model describing the transition states of the
robot working body movement zone according to the positional coordinates corresponding to the cyclic
control signals was developed, and mathematical models reflecting the interdependence of each state
were presented. Based on the mathematical models that describe these transition states and reflect the
interdependence of each state, an algorithm for controlling the movements of the industrial robot
manipulator with high accuracy and speed has been developed.
 

  • Internet ҳавола
  • DOI
  • UzSCI тизимида яратилган сана 13-11-2024
  • Ўқишлар сони 15
  • Нашр санаси 08-11-2024
  • Мақола тилиIngliz
  • Саҳифалар сони45-48
English

This article is devoted to the adaptive cyclic control of an industrial robot manipulator
on the example of moving objects with a positional trajectory. The specific features of applying the
principle of adaptive cyclic control to industrial robots are also presented. The kinematic scheme
describing the movement of the robot working body with the adaptive cycle control system and the
transition states of the working body based on limited positions in space are presented, the sequence of
movement of the manipulator links and the selection of information about the actions at individual levels
of mobility, control in the case of a variable sequence of links by positional coordinates the formation
of programs was considered. During the control process, a model describing the transition states of the
robot working body movement zone according to the positional coordinates corresponding to the cyclic
control signals was developed, and mathematical models reflecting the interdependence of each state
were presented. Based on the mathematical models that describe these transition states and reflect the
interdependence of each state, an algorithm for controlling the movements of the industrial robot
manipulator with high accuracy and speed has been developed.
 

№ Муаллифнинг исми Лавозими Ташкилот номи
1 Zaripov O.. DSc, Professor Tashkent State Technical University
2 Sevinova . . Doctoral student Tashkent State Technical University
№ Ҳавола номи
1 1. Zenkivich, S.L., Jushhenko A.S. (2000). Upravlenija robotami. osnovy upravlenija manipuljacionnymi robotami [Robot control. basics of manipulating robots control]. MGTU im. N.Je.Baumana, Moscow, 400 p. (in. Russian). 2. Glazunov, V.A. (2018). Novye mehanizmy v sovremennoj robototehnike [New mechanisms in modern robotics]. TEHANOSFERA, Moscow, 316p (in. Russian). 3. Pol, R. 1986. Modelirovanie, planirovanie traektrorij i upravlenie dvizheniem robota-manipuljatora. - M.: Nauka, — 103 s (in. Russian). 4. Dzhozef L. (2019). Izuchenie robototehniki s ispol'zovaniem Python. per. s ang. A.V.Korjagina. – M.: DMK Press, – 250 s. (in. Russian).
2 5. Igamberdiev H.Z., Sevinov Zh.U., Zaripov O.O. (2014). Reguljarnye metody i algoritmy sinteza adaptivnyh sistem upravlenija s nastraivaemymi modeljami. – T.: TashGTU, – 160 s. (in. Russian). 6. Nazarov H.N. (2019). Intellektual'nye mnogokoordinatnye mehatronnye moduli robototehnicheskih sistem // Monografija, Toshkent izd “Mashhur-Press”. –143 s. (in. Russian). 7. Jusupbekov N.R. i dr. (2015). Intellektual'nye sistemy upravlenija i prinjatie reshenij. -Tashkent: Izdatel'stvo Nacional'noj jenciklopedii Uzbekistana, – 572 s. (in. Russian). 8. Kozlov V.V., Makarychev V.P., Timofeev A.V., Jurevich E.I. (1984). Dinamika upravlenija robotami. – M.: Nuka. -336 s. (in. Russian).
3 9. Zaripov O.O., Sevinova D.U. Sevinov I.U. (2019). Synthesis Algorithms for Adaptive Process Control Systems Based on Associative Memory Technology. International Journal of Innovative Technology and Exploring Engineering (IJITEE), Vol.9 Issue 2. ISSN: 2278-3075, pp-38-42. DOI: 10.35940/ijitee.A4745.129219 10. Zaripov Oripjon Olimovich, Sevinova Dildora Usmonovna, Bobojanov Sukhrob Gayratovich. (2024)Adaptive Posision-Determination and Dynamic Model Properties Synthesis of Moving Objects With Trajectory Control System (In the Case of Multi-Link Manipulators). Transactions of the Korean Institute of Electrical Engineers, Vol. 73, № 3, pp 576 – 584. 11. Oripjon Zaripov and Dildora Sevinova. (2023). Structural and Kinematic Synthesis Algorithms of Adaptive Position-Trajectory Control Systems (In the Case of Assembly Industrial Robots) // ICoRSE 2023, LNNS 762, pp. 1–16, https://doi.org/10.1007/978-3-031-40628- 7_50.
4 12. Tadzhiev, H.H. Sevinova, D.U. (2018). Algoritmy adaptivnyh pozicionno-traektoryh sistem upravlenija podvizhnymi obektami [Algorithmic adaptive position-trajectory system control of movement object]. In: Rol' intellektual'noj molodezhi v razvitii nauki i tehniki, Sbornik dokladov respublikanskoj nauchno - tehnicheskoj konferencii. TashGTU, Tashkent, pp. 31-33. 13. Afanas'ev V.A., L. Degtjarev G., Meshhanov A.S., Sirazetdinov T.K. (2007).Sintez adaptivnogo upravlenija razvorotami letatel'nogo apparata v atmosfere / Vestn. Kazan. gos. tehn. un-ta im. A. N. Tupoleva. № 4. S. 39–42, (in. Russian).
5 14. Putov V. V. Razvitie bespoiskovyh adaptivnyh metodov i ih prilozhenija k zadacham upravlenija slozhnymi mehanicheskimi ob#ektami // Aviakosmicheskoe priborostroenie. 2003. №6. -S.31-42, (in. Russian). 15. Sevinov J.U., Mallaev A.R., Xusanov S.N. (2021) Algorithms for the Synthesis of Optimal Linear-Quadratic Stationary Controllers. In: Aliev R.A., Yusupbekov N.R., Kacprzyk J., Pedrycz W., Sadikoglu F.M. (eds) 11th World Conference “Intelligent System for Industrial Automation” (WCIS-2020). WCIS 2020. Advances in Intelligent Systems and Computing, vol 1323. Springer, Cham. https://doi.org/10.1007/978-3-030-68004-6_9.
6 16. Yusupbekov, A.N., Sevinov, J.U., Mamirov, U.F., Botirov, T.V. (2021). Synthesis Algorithms for Neural Network Regulator of Dynamic System Control. Advances in Intelligent Systems and Computing, vol 1306. pp. 723– 730. Springer, Cham. https://doi.org/10.1007/978-3-030- 64058-3_90.
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