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Application of Interval Type-2 Fuzzy Logic Control Approach to the Lower-Limb Exoskeleton

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Recent Trends on Type-2 Fuzzy Logic Systems: Theory, Methodology and Applications

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 425))

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Abstract

Fuzzy logic control methods are an integral part of control engineering and are widely used in applications such as robotics, rehabilitation, home appliances, and many more. Here, an interval type-2 fuzzy logic control-based proportional-integral-derivative (IT2-FLC-PID) control method is presented for the lower-limb exoskeleton. The intention of the use of the IT2-FLC-PID approach is to handle the system uncertainties and external disturbances encountered with the exoskeleton plant. The optimal controller parameters can be obtained using a well-known and nature-inspired optimization algorithm, the namely cuckoo search algorithm (CSA). To investigate the efficacy of the IT2-FLC-PID control scheme applied to the exoskeleton system, simulation results are compared with the traditional type-1 FLC-PID (TI-FLC-PID) and the standard PID control approach.

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References

  1. Cooper, R.A., Dicianno, B.E., Brewer, B., LoPresti, E., Ding, D., Simpson, R., Grindle, G., Wang, H.: A perspective on intelligent devices and environments in medical rehabilitation. Med. Eng. Phys. 30, 1387–1398 (2008)

    Article  Google Scholar 

  2. Zeilig, G., Weingarden, H., Zwecker, M., Dudkiewicz, I., Bloch, A., Esquenazi, A.: Safety and tolerance of the RewalkTM exoskeleton suit for ambulation by people with complete spinal cord injury: a pilot study. J. Spinal Cord Med. 35(2), 96–101 (2012)

    Article  Google Scholar 

  3. Aliman, N., Ramli, R., Haris, S.M., Amiri, M.S., Van, M.: A robust adaptive fuzzy-proportional-derivative controller for a rehabilitation lower limb exoskeleton. Eng. Sci. Technol. Int. J. 35, 101097 (2022)

    Google Scholar 

  4. Shi, D., Zhang, W., Zhang, W., Ding, X.: A review on lower limb rehabilitation exoskeleton robots. Chinese J. Mech. 32(74), 1–11 (2019)

    Google Scholar 

  5. Pinto-Fernandez, D., Torricelli, D., Sanchez-Villamanan, M.D.C., Aller, F., Mombaur, K., Conti, R., Vitiello, N., Moreno, J.C., Pons, J.L.: Performance evaluation of lower limb exoskeleton: a systematic review. IEEE Trans. Neural Syst. Rehabil. Eng. 28(7), 1573–1583 (2020)

    Article  Google Scholar 

  6. Baud, R., Manzoori, A., Ljspeert, A., Bouri, M.: Review of control strategies for lower-limb exoskeletons to assist gait. J. Neuro Eng. Rehabil 18, 119 (2021)

    Article  Google Scholar 

  7. Sharma, R., Rana, K.P.S., Kumar, V.: Performance analysis of fractional order fuzzy PID controllers applied to a robotic manipulator. Expert Syst. Appl. 41(9), 4274–4289 (2014)

    Article  Google Scholar 

  8. Chen, Z., Li, Z., Philip Chen, C.L.: Disturbance observer-based fuzzy control of uncertain MIMO mechanical systems with input nonlinearities and its application to robotic exoskeleton. IEEE Trans. Cybern. 47(4), 984–994 (2017)

    Google Scholar 

  9. Kiguchi, K., Iwami, K., Yasuda, M., Watanabe, K.: An exoskeleton robot for human shoulder joint motion assist. IEEE/ASME Trans. Mechatron. 8(1), 125–135 (2003)

    Article  Google Scholar 

  10. Yin, K., Xiang, K., Pang, M., Chen, J., Anderson, P., Yang, L.: Personalised control of robotic ankle exoskeleton through experience-based adaptive fuzzy inference. IEEE Access 7, 72221–72233 (2019)

    Article  Google Scholar 

  11. Niu, J., Song, Q., Wang, X.: Fuzzy PID control for passive lower extremity exoskeleton in swing phase. In: 2013 IEEE 4th International Conference on Electronics, Information and Emergency Communication, 15–17 Nov 2013, Beijing, China

    Google Scholar 

  12. Kong, K., Jeon, D.: Fuzzy control of a new tendon-driven exo-skeletal power assistive device. In: Proceeding, 2005 IEEE/ASME International Conference Advance Intelligent Mechatronics IEEE 2005, pp. 146–151 (2005)

    Google Scholar 

  13. Rezage, G.Al., Tokhi, M.O.: Fuzzy PID control of lower limb exoskeleton for elderly mobility. Proceedings AQTR: IEEE International Conf. on Automation, Quality and Testing, Robotics, Cluj-Napoca, Romania, 19–21 May 2016, pp. 1–6

    Google Scholar 

  14. Sharma, R., Gaur, P., Bhatt, S., Joshi, D.: Optimal fuzzy logic-based control strategy for lower-limb rehabilitation exoskeleton. Appl. Soft Comput. 105, 107226 (2021)

    Article  Google Scholar 

  15. El-Bardini, M., El-Nagar, A.M.: Interval type-2 fuzzy PID controller for uncertain nonlinear inverted pendulum system. ISA Trans. 53, 732–743 (2014)

    Article  Google Scholar 

  16. Sharma, R., Deepak, K.K., Gaur, P., Joshi, D.: An optimal interval type-2 fuzzy logic control based closed-loop drug administration to regulate the mean arterial blood pressure. Comput. Methods Programs Biomed. 185, 105167 (2020)

    Article  Google Scholar 

  17. Gaidhane, P.J., Nigam, M.J., Kumar, A., Pradhan, P.M.: Design of interval type-2 fuzzy logic precompensated PID control applied to two-DOF robotic manipulator with variable payload. ISA Trans. 89, 169–185 (2019)

    Article  Google Scholar 

  18. Kumar, A., Kumar, V.: Design of interval type-2 fractional order fuzzy logic controller for redundant robot with artificial bee colony. Arabian J. Sci. Eng. 44, 1883–1902 (2019)

    Article  Google Scholar 

  19. Sharma, R., Gaur, P., Mittal, A.P.: Performance analysis of two-degree of freedom fractional order PID controllers for robotic manipulator with payload. ISA Trans. 58, 279–291 (2015)

    Article  Google Scholar 

  20. Sharma, R., Gaur, P., Mittal, A.P.: Design of two-layered fractional order fuzzy logic controllers applied to robotic manipulator with variable payload. Appl. Soft Comput. 47, 565–576 (2016)

    Article  Google Scholar 

  21. Sharma, R., Gaur, P., Bhatt, S., Joshi, D.: Performance assessment of fuzzy logic control approach for MR-damper based-transfemoral prosthetic leg. IEEE Trans. Artif. Intell. 3(1), 53–66 (2021)

    Article  Google Scholar 

  22. Yang, Y., Huang, D., Dong, X.: Enhanced neural network control of lower limb rehabilitation exoskeleton by add-on repetitive learning. Neurocomputing 123, 256–264 (2019)

    Article  Google Scholar 

  23. Castillo, O., Melin, P.: A review on the design and optimization of interval type-2 fuzzy controllers. Appl. Soft Comput. 12, 1267–1278 (2012)

    Article  Google Scholar 

  24. Liang, Q., Mendel, J.M.: Interval type-2 fuzzy logic systems: theory and design. IEEE Trans. Fuzzy Syst. 8, 535–550 (2000)

    Article  Google Scholar 

  25. Yang, X.S., Deb, S.: Cuckoo search via Leύy flight. In: Proceedings of the World Congress on Nature & Biologically Inspired Computing, India, pp. 210–214 (2009)

    Google Scholar 

  26. Sharma, R., Bhasin, S., Gaur, P., Joshi, D.: A switching-based collaborative fractional order fuzzy logic controllers for robotic manipulators. Appl. Math. Model. 73, 228–246 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  27. Sharma, R., Gaur, P., Mittal, A.P.: Optimum design of fractional-order hybrid controller for a robotic manipulator. Arabian J. Sci. Eng. 42(2), 739–750 (2017)

    Article  Google Scholar 

  28. Yang, X.S., Deb, S.: Engineering optimization by cuckoo search. Inte. J. Math. Model. Numer. Optim. 1(4), 330–343 (2010)

    MATH  Google Scholar 

  29. Taskin, A., Kumbasar, T.: An open source Matlab/Simulink toolbox for interval type-2 fuzzy logic systems. In: Proceedings of the IEEE Symposium Series on Computational Intelligence, pp. 561–568 (2015)

    Google Scholar 

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Authors and Affiliations

  1. Department of Mechanical Engineering, Donadeo Innovation Centre for Engineering, University of Alberta, Edmonton, AB, T6G 1H9, Canada

    Richa Sharma & Hossein Rouhani

Authors
  1. Richa Sharma
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  2. Hossein Rouhani
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Correspondence to Richa Sharma .

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Editors and Affiliations

  1. Research Chair of Graduate Studies, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  2. Department of Electronics and Communication Engineering, National Institute of Technology, Patna, India

    Anupam Kumar

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Sharma, R., Rouhani, H. (2023). Application of Interval Type-2 Fuzzy Logic Control Approach to the Lower-Limb Exoskeleton. In: Castillo, O., Kumar, A. (eds) Recent Trends on Type-2 Fuzzy Logic Systems: Theory, Methodology and Applications. Studies in Fuzziness and Soft Computing, vol 425. Springer, Cham. https://doi.org/10.1007/978-3-031-26332-3_1

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