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Adaptive gain super twisting algorithm to control a knee exoskeleton disturbed by unknown bounds

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Abstract

Knee exoskeletons as wearable robots have been increasingly aimed to assist elderly and disabled people to increase their movement abilities through flexion/extension execution of the knee. In this paper, a robust controller was suggested for a new knee joint orthosis. The system is integrated with the orthosis and the human shank and has a nonlinear dynamic model. This paper presents a novel robust controller of an active orthosis for rehabilitation due to no prior knowledge on the dynamical model and unknown the flexion/extension movements as disturbances, an adaptive gain super-twisting algorithm is used to control the knee joint. It is needed to this strategy to cope with the nonlinear nature of the knee exoskeleton with disturbance and model uncertainties that is bounded with unknown bounds. The stability analysis was proven by the Lyapunov approach.

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References

  1. Herr H (2009) Exoskeletons and orthoses: classification, design challenges and future directions. J Neuro Eng Rehabil 6(1):21–30

    Article  Google Scholar 

  2. Cobb GL (1935) Walking motion. US Patent 2,010,482, August 6, 1935

  3. Toyama S, Yamamoto G (2009) Development of wearable-agri-robot ~ mechanism for agricultural work. IEEE IROS, pp 5801–5806

  4. Zoss AB, Kazerooni H, Chu A (2006) Biomechanical design of the Berkeley lower extremity exoskeleton (BLEEX). IEEE/ASME Trans Mechatron 11(2):128–138

    Article  Google Scholar 

  5. http://www.army-technology.com/features/featurefrench-hercule-robotic-exoskeleton

  6. Costa N, Bezdicek M, Brown M (2006) Joint motion control of a powered lower limb orthosis for rehabilitation. Int J Autom Comput 3(3):271–281

    Article  Google Scholar 

  7. Banala SK, Agrawal SK, Fattah A, Krishnamoorthy V, Hsu WL, Scholz J, Rudolph K (2006) Gravity-balancing leg orthosis and its performance evaluation. IEEE Trans Robot 22:1228–1239

    Article  Google Scholar 

  8. Aliman N, Ramli R, Haris SM (2017) Design and development of lower limb exoskeletons: a survey. Robot Auton Syst 95:102–116

    Article  Google Scholar 

  9. Endo K, Paluska D, Herr H (2006) A quasi-passive model of human leg function in level-ground walking. In: IEEE/RSJ international conference on intelligent robotic system. IEEE, pp 4935–4939

  10. Lee H, Kim W, Han J, Han C (2012) The technical trend of the exoskeleton robot system for human power assistance. Int J Precise Eng Manuf 13:1491–1497

    Article  Google Scholar 

  11. Feng Z, Qian J, Zhang Y, Shen L, Zhang Z, Wang Q (2007) Biomechanical design of the powered gait orthosis. In: IEEE international conference on robotic biomimetics, pp 1698–1702

  12. Diaz I, Gil JJ, Sunchez E (2011) Lower-limb robotic rehabilitation: literature review and challenges. J Robots, pp 1–11

  13. Vorobyev AA, Petrukhin AV, Zasypkina OA, Krivonozhkina PS, Pozdnyakov AM (2015) Exoskeleton as a new means in habilitation and rehabilitation of invalids (review). Sovrem Tehnol Med 7(2):185–197

    Article  Google Scholar 

  14. Ortlieb A, Olivier J, Bouri M, Bleuler H, Kuntzer T (2015) From gait measurements to design of assistive orthoses for people with neuromuscular diseases. In: IEEE international conference on rehabilitation robotics, pp 368–373

  15. Pratt JE, Krupp BT, Morse ChJ (2004) The roboKnee: an exoskeleton for enhancing strength and endurance during walking. Int J Robot Autom 3:2430–2435

    Google Scholar 

  16. Nikitczuk J, Weinberg B, Mavroidis C (2007) Control of electro-rheological fluid based resistive torque elements for use in active rehabilitation devices. Smart Mater Struct 16:418

    Article  Google Scholar 

  17. Aua S, Bernikera M, Herra H (2008) Powered ankle-foot prosthesis to assist level-ground and stair-descent gaits. Neural Netw 21:654–666

    Article  Google Scholar 

  18. Daachi ME, Madani T, Daachi B, Djouani K (2015) A radial basis function neural network adaptive controller to drive a powered lower limb knee joint orthosis. Appl Soft Comput 34:324–336

    Article  Google Scholar 

  19. Gomes M, Silveira G, Siqueira A (2011) Gait pattern adaptation for an active lower-limb orthosis based on neural networks. Adv Robot 25(15):1903–1925

    Article  Google Scholar 

  20. Kiguchi K, Tanaka T, Fukuda T (2004) Neuro-fuzzy control of a robotic exoskeleton with EMG signals. IEEE Trans Fuzzy Syst 12(4):481–490

    Article  Google Scholar 

  21. Hayashi T, Kawamoto H, Sankai Y (2005) Control method of robot suit HAL working as operator’s muscle using biological and dynamical information. In: IEEE/RSJ, international conference on intelligent robots and systems, pp 3063–3068

  22. Jezernik S, Wassink RGV, Keller T (2004) Sliding mode closed-loop control of FES controlling the shank movement. IEEE Trans Biomed Eng 51(2):263–272

    Article  Google Scholar 

  23. Banala SK, Agrawal SK (2005) Gait rehabilitation with an active leg orthosis. In: ASME proceedings, 29th mechanisms and robotics conference, pp 459–4465

  24. Madani T, Daachi B, Djouani K (2016) Non-singular terminal sliding mode controller: application to an actuated exoskeleton. Mechatronics 33:136–145

    Article  Google Scholar 

  25. Mefoued S, Mohammed S, Amirat Y (2013) Toward movement restoration of knee joint using robust control of powered orthosis. IEEE Trans Control Syst Technol 21(6)

  26. Mirrashid N, Rakhtala SM, Ghanbari M (2018) Modeling and analysis robust control design for air breathing proton exchange membrane fuel cell system via variable gain second- order sliding mode. Energy Sci Eng 6(3):126–143

    Article  Google Scholar 

  27. Evangelista C, Puleston P, Valenciaga F(2013) Variable gains super-twisting control for wind energy conversion optimization. In: 11th international workshop on variable structure systems (VSS)

  28. Leva P (1996) Adjustments to Zatsiorsky–Seluyanov’s segment inertia parameters. J Biomech 29(9):1223–1230

    Article  Google Scholar 

  29. Mefoued S, Mohammed S, Amirat Y, Fried G (2012) Sit-to-stand movement assistance using an actuated knee joint orthosis. In: IEEE RAS and EMBS international conference on biomedical robotics and biomechatronics, pp 1753–1758

  30. Gill P, Murray W (1978) Algorithms for the solution of the nonlinear least-squares problem. SIAM J Numer Anal 15(5):977–992

    Article  MathSciNet  Google Scholar 

  31. Mohammed S, Huo W, Huang J, Rifaï H, Amirat Y (2016) Nonlinear disturbance observer based sliding mode control of a human-driven knee joint orthosis. Robot Auton Syst 75:41–49

    Article  Google Scholar 

  32. Mefoued S (2015) A second order sliding mode control and a neural network to drive a knee joint actuated orthosis. Neurocomputing 155:71–79

    Article  Google Scholar 

  33. Lin F, Brandt RD, Saikalis G (2000) Self-tuning of PID controllers by adaptive interaction. In: Proceedings of the 2000 American control conference. ACC (IEEE Cat. No. 00CH36334), Chicago, IL, USA, vol 5, pp 3676–3681

  34. Mahdi M, Reza KH, Jeyraj S, Rahim NB (2014) Online adaptive power factor correction controller for DC–DC converters. In: 3rd IET international conference on clean energy and technology (CEAT), Kuching, pp 1–5

  35. Rakhtala SM, Ranjbar NA, Ghaderi R, Usai E (2015) Control of oxygen excess ratio in PEM fuel cell system using high-order sliding mode controller and observer. Turk J Electr Eng Comput Sci 23:255–278

    Article  Google Scholar 

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Authors and Affiliations

  1. Faculty of Engineering, Department of Electrical Engineering, Golestan University, Gorgan, Iran

    Seyed Mehdi Rakhtala

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  1. Seyed Mehdi Rakhtala
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Correspondence to Seyed Mehdi Rakhtala.

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Rakhtala, S.M. Adaptive gain super twisting algorithm to control a knee exoskeleton disturbed by unknown bounds. Int. J. Dynam. Control 9, 711–726 (2021). https://doi.org/10.1007/s40435-020-00686-z

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  • DOI: https://doi.org/10.1007/s40435-020-00686-z

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