Skip to main content
SpringerLink
Log in

Decentralized Fault Tolerant Control for Modular Robot Manipulators via Integral Terminal Sliding Mode and Disturbance Observer

  • Regular Papers
  • Robot and Applications
  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

A novel decentralized fault tolerant approach for modular robot manipulators (MRMs) with external disturbances is proposed via an integral terminal sliding mode and disturbance observer. First, an integral terminal sliding mode control strategy is designed for fault tolerant control of MRMs system. Next, to eliminate the effect of uncertainty, radial basis function neural networks (RBFNN) and nonlinear disturbance observers (DO) are constructed to deal with the uncertainty of MRMs system, which includes the interconnected dynamic coupling (IDC), faults, external disturbance, friction terms, and the neural network estimation errors. And then, in order to reduce the chattering, the super twist algorithm (STA) is designed to enhance the dynamic performance of MRMs system. Based on the Lyapunov theory, the stability of MRMs system is demonstrated under the proposed decentralized fault tolerant control strategy. Finally, the effectiveness and advantages of the proposed algorithm are verified by constructing computer simulation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. B. Dong, F. Zhou, K. Liu, and Y. Li, “Decentralized robust optimal control for modular robot manipulators via critic-identifier structure-based adaptive dynamic programming,” Neural Computing and Applications, vol. 32, pp. 3441–3458, September 2020.

    Article  Google Scholar 

  2. Y. Li, W. Jin, B. Ma, and B. Dong, “Adaptive dynamic programming-based decentralized guaranteed cost control for reconfigurable manipulators with uncertain environments,” Journal of Electrical Engineering and Technology, vol. 15, no. 4, pp. 2315–2330, August 2020.

    Article  Google Scholar 

  3. B. Zhao and Y. Li, “Model-free adaptive dynamic programming based near-optimal decentralized tracking control of reconfigurable manipulators,” International Journal of Control, Automation, and Systems, vol. 16, no. 2, pp. 478–490, April 2018.

    Article  Google Scholar 

  4. S. Yoo, S. Rama, B. Szewczyk, J. W. Pui, W. Le, and L. Kim, “Endoscopic capsule robots using reconfigurable modular assembly: A pilot study,” International Journal of Imaging Systems Technology, vol. 24, no. 4, pp. 359–365, 2014.

    Article  Google Scholar 

  5. R. Tommaso, C. Matteo, G. Giada, D. F. Iris, and M. Arianna, “A soft modular manipulator for minimally invasive surgery: Design and characterization of a single module,” IEEE Transactions on Robotics, vol. 32, no. 1, pp. 187–200, 2016.

    Article  Google Scholar 

  6. C. H. Belke and J. Paik, “Mori: A modular origami robot,” IEEE/ASME Transactions on Mechatronics, vol. 22, no. 5, pp. 2153–2164, April 2017.

    Article  Google Scholar 

  7. Y. Chang, C. Wu, and H. Lin, “Adaptive distributed fault-tolerant formation control for multi-robot systems under partial loss of actuator effectiveness,” International Journal of Control, Automation, and Systems, vol. 16, pp. 2114–2124, September 2018.

    Article  Google Scholar 

  8. Z. Anjum and Y. Guo, “Finite time fractional-order adaptive backstepping fault tolerant control of robotic manipulator,” International Journal of Control, Automation, and Systems, vol. 19, no. 1, pp. 301–310, August 2021.

    Article  Google Scholar 

  9. J. Gong, B. Jiang, and Q. Shen, “Distributed-observer-based fault tolerant control design for nonlinear multiagent systems,” International Journal of Control, Automation, and Systems, vol. 17, no. 12, pp. 3149–3157, 2019.

    Article  Google Scholar 

  10. X. Liu, M. Zhang, Y. Wang, and E. Rogers, “Design and experimental validation of an adaptive sliding mode observer-based fault-tolerant control for underwater vehicles,” IEEE Transactions on Control Systems Technology, vol. 27, no. 6, pp. 2655–2662, October 2018.

    Article  Google Scholar 

  11. M. Van, M. Mavrovouniotis, and S. S. Ge, “An adaptive backstepping nonsingular fast terminal sliding mode control for robust fault tolerant control of robot manipulators,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 49, no.7, pp. 1448–1458, 2018.

    Article  Google Scholar 

  12. D. S. Jovan,“Passive fault tolerant perfect tracking with additive faults,” Automatica, vol. 87, pp. 432–436, 2018.

    Article  MathSciNet  MATH  Google Scholar 

  13. W. Ao, Y. Song, and C. Wen, “Adaptive robust fault tolerant control design for a class of nonlinear uncertain MIMO systems with quantization,” ISA Transactions, vol. 68, pp. 63–72, May 2017.

    Article  Google Scholar 

  14. B. Zhao, C. Li, D. Liu, and Y. Li, “Decentralized sliding mode observer based dual closed-loop fault tolerant control for reconfigurable manipulator against actuator failure,” PloS one, vol. 10, no. 7, pp. 1–17, July 2015.

    Article  Google Scholar 

  15. R. Muradore, “A PLS-based statistical approach for dault detection and isolation of robotic manipulators,” IEEE Transactions on Industrial Electronics, vol. 59, no. 8, pp. 3167–3175, September 2012.

    Article  Google Scholar 

  16. Z. Jin, Y. Hu, C. Li, and C. Sun, “Event-triggered fault detection and diagnosis for networked systems with sensor and actuator faults,” IEEE Access, vol.7, pp. 95857–95866, July 2019.

    Article  Google Scholar 

  17. Y. Li, F. Zhou, and B. Zhao, “Dynamic output feedback based active decentralized fault-tolerant control for reconfigurable manipulator with concurrent failures,” Mathematical Problems in Engineering, pp. 1–14, March 2015.

  18. B. Zhao and Y. Li, “Local joint information based active fault tolerant control for reconfigurable manipulator,” Nonlinear Dynamics, vol. 77, no. 3, pp. 859–876, March 2014.

    Article  MathSciNet  MATH  Google Scholar 

  19. M. Van, S. S. Ge, and H. Ren, “Finite time fault tolerant control for robot manipulators using time delay estimation and continuous nonsingular fast terminal sliding mode control,” IEEE Transactions on Cybernetics, vol. 47, no. 7, pp. 1681–1693, 2017.

    Article  Google Scholar 

  20. F. Zhou, Y. Li, and G. Liu, “Robust decentralized force/position fault-tolerant control for constrained reconfifigurable manipulators without torque sensing,” Nonlinear Dynamics, vol. 89, pp. 955–969, April 2017.

    Article  MATH  Google Scholar 

  21. Q. Meng, T. Zhang, J. He, and J. Song, “Adaptive vector sliding mode fault-tolerant control of the uncertain Stewart platform based on position measurements only,” Robotica, vol. 34, no. 6, pp. 1297–1321, September 2016.

    Article  Google Scholar 

  22. G. Tao, S. Chen, and S. M. Joshi, “An adaptive actuator failure compensation controller using output feedback,” IEEE Transactions on Automatic Control, vol. 47, no. 3, pp. 506–511, August 2002.

    Article  MathSciNet  MATH  Google Scholar 

  23. Z. Mao, X. Yan, B. Jiang, and M. Chen, “Adaptive fault-tolerant sliding-mode control for high-speed trains with actuator faults and uncertainties,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 6, pp. 2449–2460, June 2020.

    Article  Google Scholar 

  24. H. Dong, X. Lin, S. Gao, B. Cai, and B. Ning, “Neural networks-based sliding mode fault-tolerant control for high-speed trains with bounded parameters and actuator faults,” IEEE Transactions on Vehicular Technology, vol. 69, no. 2, pp. 1353–1362, February 2020.

    Article  Google Scholar 

  25. D. I. Martinez, J. Rubio, T. M. Vargas, V. Garcia, and C. Aguilar-Ibanez, “Stabilization of robots with a regulator containing the sigmoid mapping,” IEEE Access, vol. 8, no. 1, pp. 89479–89488, May 2020.

    Article  Google Scholar 

  26. D. I. Martinez, J. Rubio, V. Garcia, T. M. Vargas, and C. Aguilar-Ibanez, “Transformed structural properties method to determine the controllability and observability of robots,” Applied Sciences, vol. 11, no. 7, p. 3082, March 2021.

    Article  Google Scholar 

  27. J. O. Escobedo-Alva, E. C. Garcia-Estrada, L. A. Paramo-Carranza, J. A. Meda-Campana, and R. Tapia-Herrera, “Theoretical application of a hybrid observer on altitude tracking of quadrotor losing GPS signal,” IEEE Access, vol. 6, pp. 76900–76908, November 2018.

    Article  Google Scholar 

  28. D. I. Martinez, J. Rubio, A. Aguilar, J. Pacheco, G. J. Gutierrez, V. Garcia, T. M. Vargas, G. Ochoa, D. R. Cruz, and C. F. Juarez, “Stabilization of two electricity generators,” Complexity, vol. 2020, pp. 1–13, December 2020.

    Article  Google Scholar 

  29. C. Aguilar-Ibanez and M. S. Suarez-Castanon, “A trajectory planning based controller to regulate an uncertain 3D overhead crane system,” International Journal of Applied Mathematics and Computer Science, vol. 29, no. 4, pp. 693–702, December 2019.

    Article  MathSciNet  MATH  Google Scholar 

  30. J. R. García-Sánchez, S. Tavera-Mosqueda, R. Silva-Ortigoza, V. M. Hernández-Guzmán, J. Sandoval-Gutiérrez, M. Marcelino-Aranda, H. Taud, and M. Marciano-Melchor, “Robust switched tracking control for wheeled mobile robots considering the actuators and drivers,” Sensors, vol. 18, p. 4316, December 2018.

    Article  Google Scholar 

  31. S. Jung, “Improvement of tracking control of a sliding mode controller for robot manipulators by a neural network,” International Journal of Control, Automation, and Systems, vol. 16, no. 2, pp. 937–943, April 2018.

    Article  Google Scholar 

  32. C. Sun, G. Gong, and H. Yang, “Sliding mode control with adaptive fuzzy immune feedback reaching law,” International Journal of Control, Automation, and Systems, vol. 18, pp. 363–373, February 2020.

    Article  Google Scholar 

  33. M. Van and S. S. Ge, “Adaptive fuzzy integral sliding mode control for robust fault tolerant control of robot manipulators with disturbance observer,” IEEE Transactions on Fuzzy Systems, vol. 29, no. 5, pp. 1284–1296, May 2021.

    Article  Google Scholar 

  34. M. B. R. Neila and D. Tarak, “Adaptive terminal sliding mode control for rigid robotic manipulators,” International Journal of Control, Automation, and Systems, vol. 8, no. 2, pp. 215–220, May 2011.

    Google Scholar 

  35. Y. Li, Z. Lu, F. Zhou, B. Dong, K. Liu, and Y. Li, “Decentralized trajectory tracking control for modular and reconfigurable robots with torque sensor: Adaptive terminal sliding control-based approach,” Journal of Dynamic Systems Measurement and Control, vol. 141, no. 6, pp. 61003–61012, January 2019.

    Article  Google Scholar 

  36. S. Xu, C. Chen, and Z. Wu, “Study of nonsingular fast terminal sliding-mode fault-tolerant control,” IEEE Transactions on Industrial Electronics, vol. 62, no. 6, pp. 3906–3913, February 2015.

    Google Scholar 

  37. Q. Le and H. Kang, “Finite-time fault-tolerant control for a robot manipulator based on synchronous terminal sliding mode control,” Applied Sciences, vol. 10, no. 9, p. 2998, April 2020.

    Article  Google Scholar 

  38. Y. Xia, W. Xie, and J. Ma, “Research on trajectory tracking control of manipulator based on modified terminal sliding mode with double power reaching law,” International Journal of Advanced Robotic Systems, vol. 16, no. 3, pp. 1–10, May 2019.

    Article  Google Scholar 

  39. L. Zhao and Y. Jia, “Decentralized adaptive attitude synchronization control for spacecraft formation using nonsingular fast terminal sliding mode,” Nonlinear Dynamics, vol. 78, no. 4, pp. 2779–2794, August 2014.

    Article  MATH  Google Scholar 

  40. L. Wang, Y. Sheng, and X. Liu, “A novel adaptive highorder sliding mode control based on integral sliding mode,” International Journal of Control, Automation, and Systems, vol. 12, no. 3, pp. 459–472, May 2014.

    Article  Google Scholar 

  41. C. S. Jeong, J. S. Kim, and S. I. Han, “Tracking error constrained super-twisting sliding mode control for robotic systems,” International Journal of Control, Automation, and Systems, vol. 16, no. 2, pp. 804–814, March 2018.

    Article  Google Scholar 

  42. M. Rahmani, H. Komijani, and M. H. Rahman, “New sliding mode control of 2-DOF robot manipulator based on extended grey wolf optimizer,” International Journal of Control, Automation, and Systems, vol. 18, no. 9, pp. 1572–1580, January 2020.

    Article  Google Scholar 

  43. G. Liu, S. Abdul, and A. A. Goldenberg, “Distributed control of modular and reconfigurable robot with torque sensing,” Robotica, vol. 26, no. 1, pp. 75–84, January 2008.

    Article  Google Scholar 

  44. J. Imura, T. Sugie, Y. Yokokohji, and T. Yoshikawa, “Robust control of robot manipulators based on joint torque sensor information,” Proc. of IEEE/RSJ International Workshop on Intelligent Robots and System, Osaka, Japan, pp. 344–349, November 1991.

  45. D. S. Mitrinović, J. E. Pečarić, and A. M. Fink, Young’s Inequality, Springer Netherlands, vol. 61, pp. 379–389, 1993.

    Google Scholar 

  46. Z. Chen, Z. Li, and C. Chen, “Disturbance observer-based fuzzy control of uncertain MIMO mechanical systems with input nonlinearities and its application to robotic exoskeleton,” IEEE Transactions on Cybernetics, vol. 47, no. 4, pp. 984–994, March 2016.

    Article  Google Scholar 

  47. J. Yang, W. Chen, and S. Li, “Non-linear disturbance observer-based robust control for systems with mismatched disturbances/uncertainties,” IET Control Theory and Applications, vol. 5, no. 18, pp. 2053–2062, December 2011.

    Article  MathSciNet  Google Scholar 

  48. B. Z. Guo and F. F. Jin, “Output feedback stabilization for one-dimensional wave equation subject to boundary disturbance,” IEEE Transactions on Automatic Control, vol. 60, no. 3, pp. 824–830, July 2015.

    Article  MathSciNet  MATH  Google Scholar 

  49. W. Sun, J. W. Lin, S. F. Su, N. Wang, and J. E. Meng, “Reduced adaptive fuzzy decoupling control for lower limb exoskeleton,” IEEE Transactions on Cybernetics, vol. 51, no. 3, pp. 1099–1109, February 2020.

    Article  Google Scholar 

  50. S. Diao, W. Sun, S. F. Su, and J. Xia, “Adaptive fuzzy event-triggered control for single-link flexible-joint robots with actuator failures,” IEEE Transactions on Cybernetics, vol. 52, no. 8, pp. 7231–3241, 2022.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electrical and Computer Engineering, Changchun University of Technology, Changchun, 130012, China

    Zengpeng Lu, Yan Li & Yuanchun Li

  2. Changchun Branch of China United Communications Co., Ltd, Changchun, 130012, China

    Xirui Fan

Authors
  1. Zengpeng Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xirui Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuanchun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuanchun Li.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This work is supported by the National Natural Science Foundation of China (Grant no. 61773075 and 61703055), the Scientific Technological Development Plan Project in Jilin Province of China (Grant nos. 20200801056GH, 20200404208YY, and 20190103004JH), and the Science and Technology project of Jilin Provincial Education Department of China during the 13th Five-Year Plan Period (JJKH20200672KJ, JJKH20200673KJ, JJKH20210767KJ, and JJKH20200674KJ).

Zengpeng Lu received his B.S. and M.S. degrees from Changchun University of Technology, China, in 2017 and 2020, respectively. He is currently working towards a Ph.D. degree in the Department of Mechanical Engineering, Changchun University of Technology, China. His research interests include intelligent mechanical, robot control, and fault tolerant control.

Yan Li received his B.E. degree from the Changchun University of Technology, Changchun, China, in 2001, an M.S. degree from Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China, in 2006, and a Ph.D. degree from the Changchun University of Technology, China, in 2020. His research interests include intelligent mechanical and robot control.

Xirui Fan received her M.S. degree in electrical engineering from Changchun University of Technology, Changchun, China, in 2020, where she works in Changchun Branch of China United Communications Co., Ltd. Her research interests include intelligent control and adaptive control.

Yuanchun Li received his M.S. and Ph.D. degrees from Harbin Institute of Technology, China, in 1987 and 1990, respectively. He is currently a Professor in Changchun University of Technology, China. He is also a Professor in Jilin University, China. His research interest covers complex system modeling, intelligent mechanical, and robot control.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, Z., Li, Y., Fan, X. et al. Decentralized Fault Tolerant Control for Modular Robot Manipulators via Integral Terminal Sliding Mode and Disturbance Observer. Int. J. Control Autom. Syst. 20, 3274–3284 (2022). https://doi.org/10.1007/s12555-021-0287-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-021-0287-6

Keywords

Search

Navigation