Performance evaluation of an adaptive fractional-order fuzzy PID controller on three-link robotic manipulator system

Sweta; Vinay Kumar Deolia; Jitendra Kumar

doi:10.2478/jee-2026-0004

Abstract

Because of their adaptability, three-link robotic manipulator (TLRM) devices are frequently used in industrial automation; yet, their operational complexity makes precise control difficult. In order to improve trajectory tracking along the X and Y directions, an adaptive fractional-order fuzzy PID (AFOFPID) controller is suggested. The optimisation criterion is a weighted mixture of the integral of absolute error (IAE) and the integral of absolute changes in controller output (IACCO), and the controller parameters are adjusted using the Cuckoo Search Algorithm (CSA). To manage changes in system dynamics, the AFOFPID combines a fuzzy logic structure with an adaptive mechanism, and the fractional-order component enhances stability and robustness even further.

References

K. Jayaswal, D. K. Palwalia, and S. Kumar, “Analysis of robust control method for the flexible manipulator in reliable operation of medical robots during COVID-19 pandemic,” Microsyst. Technol., vol. 9, no. Romanov, 2020, doi: 10.1007/s00542-020-05028-9.
Search in Google Scholar Back to article
K. Jayaswal, D. K. Palwalia, and S. Kumar, “Performance investigation of PID controller in trajectory control of two-link robotic manipulator in medical robots,” J. Interdiscip. Math., vol. 24, no. 2, pp. 467–478, Feb. 2021, doi: 10.1080/09720502.2021.1893444.
Search in Google Scholar Back to article
P. Tripathi, J. Kumar, and V. K. Deolia, “Trajectory Tracking Analysis of Fractional-Order Nonlinear PID Controller for Single Link Robotic Manipulator System BT - Proceedings of Fourth International Conference on Computer and Communication Technologies,” 2023, pp. 443–452.
Search in Google Scholar Back to article
Sweta, J. Kumar, and V. K. Deolia, “Investigation of Fractional-Order Nonlinear PID Controller for Three-link Robotic Manipulator System,” in 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2023, pp. 1–7, doi: 10.1109/ICCCNT56998.2023.10307476.
Search in Google Scholar Back to article
D. Gupta, V. Goyal, and J. Kumar, “Comparative performance analysis of fractional-order nonlinear PID controller for complex surge tank system: tuning through machine learning control approach,” Multimed. Tools Appl., 2024, doi: 10.1007/s11042-024-18427-1.
Search in Google Scholar Back to article
J. Kumar, V. Kumar, and K. P. S. Rana, “Fractional-order self-tuned fuzzy PID controller for three-link robotic manipulator system,” Neural Comput. Appl., vol. 32, no. 11, pp. 7235–7257, 2020, doi: 10.1007/s00521-019-04215-8.
Search in Google Scholar Back to article
L. A. Zadeh, “Toward a Theory of Fuzzy Systems. Aspect Network and System Theory,” New York Rinehart Winst., 1971.
Search in Google Scholar Back to article
E. H. Mamdani and S. Assilian, “An experiment in linguistic synthesis with a fuzzy logic controller,” Int. J. Man. Mach. Stud., vol. 7, no. 1, pp. 1–13, 1975, doi: https://doi.org/10.1016/S0020-7373(75)80002-2.
Search in Google Scholar Back to article
K. Khorasani, “Adaptive control of flexible joint robots,” in Proceedings. 1991 IEEE International Conference on Robotics and Automation, 1991, pp. 2127–2134 vol.3, doi: 10.1109/ROBOT.1991.131942.
Search in Google Scholar Back to article
R. K. Mudi and N. R. Pal, “A note on fuzzy PI-type controllers with resetting action,” Fuzzy Sets Syst., vol. 121, no. 1, pp. 149–159, 2001, doi: https://doi.org/10.1016/S0165-0114(99)00143-8.
Search in Google Scholar Back to article
H. A. Malki, D. Misir, D. Feigenspan, and G. Chen, “Fuzzy PID control of a flexible-joint robot arm with uncertainties from time-varying loads,” IEEE Trans. Control Syst. Technol., vol. 5, no. 3, pp. 371–378, 1997, doi: 10.1109/87.572133.
Search in Google Scholar Back to article
A. Koivo and T.-H. Guo, “Adaptive linear controller for robotic manipulators,” IEEE Trans. Automat. Contr., vol. 28, no. 2, pp. 162–171, 1983, doi: 10.1109/TAC.1983.1103211.
Search in Google Scholar Back to article
J. Kumar, D. Gupta, and V. Goyal, “Nonlinear PID Controller for Three-Link Robotic Manipulator System: A Comprehensive Approach BT - Proceedings of International Conference on Communication and Artificial Intelligence,” 2022, pp. 137–152.
Search in Google Scholar Back to article
R. Sharma, K. P. S. Rana, and V. Kumar, “Performance analysis of fractional order fuzzy PID controllers applied to a robotic manipulator,” Expert Syst. Appl., vol. 41, no. 9, pp. 4274–4289, 2014, doi: 10.1016/j.eswa.2013.12.030.
Search in Google Scholar Back to article
C. Yeroglu and N. Tan, “Classical controller design techniques for fractional order case,” ISA Trans., vol. 50, no. 3, pp. 461–472, 2011, doi: https://doi.org/10.1016/j.isatra.2011.03.004.
Search in Google Scholar Back to article
J. Kumar, V. Goyal, and D. Gupta, “Reliable Incorporation of Robust Fractional-Order Nonlinear PID Controller into Integrated Power System Using Gray Wolf Optimization Method BT - Advances in Data and Information Sciences,” 2023, pp. 333–343.
Search in Google Scholar Back to article
V. Kumar, K. P. S. Rana, J. Kumar, and P. Mishra, “Self-tuned robust fractional order fuzzy PD controller for uncertain and nonlinear active suspension system,” Neural Comput. Appl., vol. 30, no. 6, pp. 1827–1843, 2018, doi: 10.1007/s00521-016-2774-x.
Search in Google Scholar Back to article
C. C. Lee, “Fuzzy logic in control systems: fuzzy logic controller. I,” IEEE Trans. Syst. Man. Cybern., vol. 20, no. 2, pp. 404–418, 1990, doi: 10.1109/21.52551.
Search in Google Scholar Back to article
A. Mourad and Z. Youcef, “Fuzzy-PI Controller Tuned With ICA: applied to 2 DOF robot control trajectory,” in 2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT), 2022, pp. 1–6, doi: 10.1109/ICAT54566.2022.9811113.
Search in Google Scholar Back to article
A. Agrawal, V. Goyal, and P. Mishra, “Comparative Study of Fuzzy PID and PID Controller Optimized with Spider Monkey Optimization for a Robotic Manipulator System,” Recent Adv. Comput. Sci. Commun. (Formerly Recent Patents Comput. Sci., vol. 14, no. 4, 2021.
Search in Google Scholar Back to article
L. A. Zadeh, “Fuzzy sets,” Inf. Control, vol. 8, no. 3, pp. 338–353, 1965, doi: https://doi.org/10.1016/S0019-9958(65)90241-X.
Search in Google Scholar Back to article
J. Kumar, V. Kumar, and K. P. S. Rana, “A fractional order fuzzy PD+I controller for three-link electrically driven rigid robotic manipulator system,” J. Intell. Fuzzy Syst., vol. 35, pp. 5287–5299, 2018, doi: 10.3233/JIFS-169812.
Search in Google Scholar Back to article
X.-S. Yang and S. Deb, “Cuckoo search: recent advances and applications,” Neural Comput. Appl., vol. 24, no. 1, pp. 169–174, 2014, doi: 10.1007/s00521-013-1367-1.
Search in Google Scholar Back to article
K. Deb, “An introduction to genetic algorithms,” Sadhana, vol. 24, no. 4, pp. 293–315, 1999, doi: 10.1007/BF02823145.
Search in Google Scholar Back to article
R. M. Ramadan and R. F. Abdel-Kader, “Particle swarm optimization for human face recognition,” in 2009 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2009, pp. 579–584, doi: 10.1109/ISSPIT.2009.5407518.
Search in Google Scholar Back to article

Performance evaluation of an adaptive fractional-order fuzzy PID controller on three-link robotic manipulator system

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