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FUZZY LOGIC CONTROL IN ROBOT MANIPULATORS: A COMPARATIVE ANALYSIS WITH BOOLEAN LOGIC

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Scientific and technical journal "Digital Technologies in Industry"

Scientific and technical journal "Digital Technologies in Industry"

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ARTICLE ANNOTATION

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Robot manipulators encounter significant control challenges stemming from nonlinear dynamics, parametric uncertainties, and external disturbances. While Boolean logic-based controllers operate through precise binary thresholds, fuzzy logic control utilizes linguistic rules and graded membership to emulate human decision-making. This paper examines both control paradigms, detailing theoretical foundations and practical implementation for a 2-DOF manipulator. Quantitative comparisons reveal fuzzy logic’s superior adaptability in trajectory tracking and disturbance rejection, while Boolean methods maintain advantages in computational efficiency. The study concludes with controlled selection guidelines based on application-specific requirements.

AUTHORS

A.Egamberdiyev

Namangan davlat texnologiya universiteti

SH.Jo'rayev

Namangan davlat texnologiya universiteti

Tags

# нечеткая логика# fuzzy logic# nonlinear dynamics# PID controller# нелинейная динамика# адаптивное управление# adaptive control# Noaniq mantiq# Boolean control# Robot manipulator# Membership functions# Trajectory tracking# Булево управление# Робот-манипулятор# PID-контроллер# Функции принадлежности# Траектория отслеживания# Mantiqiy boshqaruv# Robot manipulyator# PID kontroller# Nochiziqli dinamika# Tegishlilik funksiyalari# Moslashuvchan boshqaruv# Kuzatuv trayektoriyasi

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Article Identifiers

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https://eroi.uz/11.0032/A0126-0070

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References

[1] Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X

[2] Lee, C. C. (1990). Fuzzy logic in control systems: Fuzzy logic controller. IEEE Transactions on Systems, Man, and Cybernetics, 20(2), 404–435. https://doi.org/10.1109/21.52551

[3] Spong, M. W., Hutchinson, S., & Vidyasagar, M. (2006). Robot modeling and control. Wiley. https://www.wiley.com/en-us/Robot+Modeling+and+Control-p-9780471649908

[4] Passino, K. M., & Yurkovich, S. (1998). Fuzzy control. Addison-Wesley. https://www.pearson.com/us/higher-education/program/Passino-Fuzzy-Control/PGM228476.html

[5] Li, T.-H. S., et al. (2020). Adaptive fuzzy hierarchical sliding-mode control for robot manipulators. IEEE Transactions on Industrial Electronics, 67(9), 7329–7340. https://doi.org/10.1109/TIE.2019.2938470

[6] Craig, J. J. (2018). Introduction to robotics: Mechanics and control (4th ed.). Pearson.

[7] Marquez, H. J. (2003). Nonlinear control systems: Analysis and design. Wiley.

[1] Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X

[2] Lee, C. C. (1990). Fuzzy logic in control systems: Fuzzy logic controller. IEEE Transactions on Systems, Man, and Cybernetics, 20(2), 404–435. https://doi.org/10.1109/21.52551

[3] Spong, M. W., Hutchinson, S., & Vidyasagar, M. (2006). Robot modeling and control. Wiley. https://www.wiley.com/en-us/Robot+Modeling+and+Control-p-9780471649908

[4] Passino, K. M., & Yurkovich, S. (1998). Fuzzy control. Addison-Wesley. https://www.pearson.com/us/higher-education/program/Passino-Fuzzy-Control/PGM228476.html

[5] Li, T.-H. S., et al. (2020). Adaptive fuzzy hierarchical sliding-mode control for robot manipulators. IEEE Transactions on Industrial Electronics, 67(9), 7329–7340. https://doi.org/10.1109/TIE.2019.2938470

[6] Craig, J. J. (2018). Introduction to robotics: Mechanics and control (4th ed.). Pearson.

[7] Marquez, H. J. (2003). Nonlinear control systems: Analysis and design. Wiley.