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Adaptive robust self-tuning PID fault-tolerant control for robot manipulators

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Abstract

In this research, by combining the filtered tracking error and the proportional–derivative–integral (PID) techniques, a novel of adaptive robust PID strategy has been explored for the robot manipulators (RM) system in presence of faults. In the proposed control system, the PID gains are adaptively self-updated to deal with time-varying uncertainties (the unknown RM dynamics, instantaneous faults, and disturbances) that are fully estimated by two adaptive estimators. In addition, in order to enhance the control robustness, a smooth robust compensator is also designed for decreasing the inevitable approximating/updating errors caused by uncertain faults, as well as limitation of the chattering phenomenon. Moreover, all designed updating/estimating algorithms are carried out online in considering of the Lyapunov stability criteria. The compared numerical simulation results are considered to verify effectiveness of the proposed RM fault control system.

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References

  1. Yu W, Rosen J (2013) Neural PID control of robot manipulators with application to an upper limb exoskeleton. IEEE Cybern 43(2):673–684

    Article  Google Scholar 

  2. ThangLong M, YaoNan W (2014) Adaptive position tracking control system based on recurrent fuzzy wavelet neural networks for robot manipulators. Proc Inst Mech Eng Part I J Syst Control Eng 228(7):500–520

  3. ThangLong M, YaoNan W (2014) Adaptive-WFCNNs-backstepping force/motion control system for mobile-manipulator robot. Kybernetes 43(2):281–306

    Article  Google Scholar 

  4. Dumlu A, Erenturk K (2014) Trajectory tracking control for a 3-dof parallel manipulator using fractional-order PiλDμ control. IEEE Trans Ind Electron 61(7):3417–3426

    Article  Google Scholar 

  5. Guo D, Xu F, Yan L (2018) New pseudoinverse-based path-planning scheme with PID characteristic for redundant robot manipulators in the presence of noise. IEEE Trans Control Syst Technol 26(6):2008–2019

    Article  Google Scholar 

  6. Khalaji AK (2019) PID-based target tracking control of a tractor-trailer mobile robot. Proc Inst Mech Eng Part C J Mech Eng Sci 233(13):4776–4787

  7. Khan AH, Li S (2020) Sliding mode control with PID sliding surface for active vibration damping of pneumatically actuated soft robots. IEEE Access 8:88793–88800

    Article  Google Scholar 

  8. Lee J, Chang PH, Yu B, Jin M (2020) An adaptive PID Control for robot manipulators under substantial payload variations. IEEE Access 8:162261–162270

    Article  Google Scholar 

  9. Niu G, Qu C (2020) Global asymptotic nonlinear PID control with a new generalized saturation function. IEEE Access 8:210513–210531

    Article  Google Scholar 

  10. Meza JL, Santibanez V, Soto R, Llama MA (2012) Fuzzy self-tuning PID semiglobal regulator for robot manipulators. IEEE Trans Ind Electron 59(6):2709–2717

    Article  Google Scholar 

  11. de Jesus Rubio J, Cruz P, Paramo LA, Meda JA, Mujica D, Ortigoza RS (2016) PID anti-vibration control of a robotic arm. IEEE Latin America Trans 14(7):3144–3150

    Article  Google Scholar 

  12. Freire EO, Rossomando FG, Soria CM (2016) Self-tuning of a neuro-adaptive PID controller for a SCARA robot based on neural network. IEEE Latin America Trans 16(5):1364–1374

    Article  Google Scholar 

  13. Pan Y, Li X, Yu H (2019) Efficient PID tracking control of robotic manipulators driven by compliant actuators. IEEE Trans Control Syst Technol 27(2):915–922

    Article  Google Scholar 

  14. Prada-Jiménez V, Niáo-Suaréz PA, Portilla-Flores EA, Mauledoux-Monroy MF (2019) Tuning a PD+ controller by means of dynamic optimization in a mobile manipulator with coupled dynamics. IEEE Access 7:124712–124726

    Article  Google Scholar 

  15. Van M, Do XP, Mavrovouniotic M (2020) Self-tuning fuzzy PID-nonsingular fast terminal sliding mode control for robust fault tolerant control of robot manipulators. ISA Trans 96:60–68

    Article  PubMed  Google Scholar 

  16. Shi JZ (2020) A fractional order general type-2 fuzzy PID controller design algorithm. IEEE Access 8:52151–52172

    Article  Google Scholar 

  17. Karami M, Tavakolpour-Saleh AR, Norouzi A (2020) Optimal nonlinear PID control of a micro-robot equipped with vibratory actuator using ant colony algorithm: simulation and experiment. J Intell Robot Syst 99:773–796

    Article  Google Scholar 

  18. Dhyani A, Panda MK, Jha B (2020) Design of an evolving fuzzy-PID controller for optimal trajectory control of a 7-DOF redundant manipulator with prioritized sub-tasks. Exp Syst Appl 162

  19. Mohammadi A, Ryu JC (2020) Neural network-based PID compensation for nonlinear systems: ball-on-plate example. Int J Dyn Control 8:178–188

    Article  MathSciNet  Google Scholar 

  20. ThangLong M (2021) Hybrid adaptive tracking control method for mobile manipulator robot based on proportional–integral–derivative technique. Proc Inst Mech Eng Part C J Mech Eng Sci 235(22):6463–6480

  21. Wu C, Liu J, Xiong Y, Wu L (2018) Observer-based adaptive fault-tolerant tracking control of nonlinear nonstrict-feedback systems. IEEE Trans Neural Netw Learn Syst 29(7):3022–3033

    MathSciNet  PubMed  Google Scholar 

  22. Van M, Mavrovouniotis M, Ge SS (2019) An adaptive backstepping nonsingular fast terminal sliding mode control for robust fault tolerant control of robot manipulators. IEEE Trans Syst Man Cybern Syst 49(7):1448–1458

    Article  Google Scholar 

  23. Hwang C, Yu W (2020) Tracking and cooperative designs of robot manipulators using adaptive fixed-time fault-tolerant constraint control. IEEE Acess 8:56415–56428

    Article  ADS  Google Scholar 

  24. Liu D, Yang Y, Li L, Ding SX (2020) Control performance-based fault-tolerant control strategy for singular systems. IEEE Trans Syst Man Cybern Syst 50(7):2398–2407

    Article  Google Scholar 

  25. Zhang S, Yang P, Kong L, Chen W, Fu Q, Peng K (2021) Neural networks-based fault tolerant control of a robot via fast terminal sliding mode. IEEE Trans Syst Man Cybern Syst 51(7):4091–4101

    Article  Google Scholar 

  26. Wang H, Kang Y, Yao L, Wang H, Gao Z (2021) Fault diagnosis and fault tolerant control for T-S fuzzy stochastic distribution systems subject to sensor and actuator faults. IEEE Trans Fuzzy Syst 29(11):3561–3569

    Article  Google Scholar 

  27. Lewis FL, Liu K, Yesildirek A (1996) Neural net robot controller with guaranteed tracking performance. IEEE Trans Neural Netw 6(3):703–713

    Article  Google Scholar 

  28. Slotine JJE, Li W (1991) Applied nonlinear control. Prentice-Hall, Englewood Cliffs

    Google Scholar 

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Funding

This work was supported by the Industrial University of Ho Chi Minh City (IUH), Vietnam, under Grant number 528/QĐ-ĐHCN, 01/03/2022.

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Authors and Affiliations

  1. Faculty of Electronics Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Mai Thang Long

  2. College of Electrical and Information Engineering, Hunan University, Changsha, Hunan, People’s Republic of China

    Wang Yao Nan

  3. Faculty of Electrical and Electronics Engineering, HCMC University of Technology and Education, Ho Chi Minh City, Vietnam

    Nguyen Vinh Quan

Authors
  1. Mai Thang Long
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  2. Wang Yao Nan
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  3. Nguyen Vinh Quan
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Dr. Mai Thang Long, Prof. Wang Yao Nan and Dr. Nguyen Vinh Quan. The first draft of the manuscript was written by Dr. Mai Thang Long, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Mai Thang Long.

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The authors have no relevant financial or non-financial interests to disclose.

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Long, M.T., Nan, W.Y. & Quan, N.V. Adaptive robust self-tuning PID fault-tolerant control for robot manipulators. Int. J. Dynam. Control 12, 477–485 (2024). https://doi.org/10.1007/s40435-023-01197-3

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  • DOI: https://doi.org/10.1007/s40435-023-01197-3

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