Advertisement

Journal of Zhejiang University SCIENCE C

, Volume 15, Issue 4, pp 275–283 | Cite as

Human-machine interaction force control: using a model-referenced adaptive impedance device to control an index finger exoskeleton

  • Qian Bi
  • Can-jun Yang
Article

Abstract

Exoskeleton robots and their control methods have been extensively developed to aid post-stroke rehabilitation. Most of the existing methods using linear controllers are designed for position control and are not suitable for human-machine interaction (HMI) force control, as the interaction system between the human body and exoskeleton is uncertain and nonlinear. We present an approach for HMI force control via model reference adaptive impedance control (MRAIC) to solve this problem in case of index finger exoskeleton control. First, a dynamic HMI model, which is based on a position control inner loop, is formulated. Second, the theoretical MRAC framework is implemented in the control system. Then, the adaptive controllers are designed according to the Lyapunov stability theory. To verify the performance of the proposed method, we compare it with a proportional-integral-derivative (PID) method in the time domain with real experiments and in the frequency domain with simulations. The results illustrate the effectiveness and robustness of the proposed method in solving the nonlinear HMI force control problem in hand exoskeleton.

Key words

Interaction force Adaptive control Exoskeleton Human-machine interaction (HMI) Impedance 

CLC number

TP242.3 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Azzurra, C., Nicola, V., Francesco, G., et al., 2012. Mechatronic design and characterization of the index finger module of a hand exoskeleton for post-stroke rehabilitation. IEEE/ASME Trans. Mechatron., 17(5):884–894. [doi:10.1109/TMECH.2011.2144614]CrossRefGoogle Scholar
  2. Bi, Q., Yang, C.J., Deng, X.L., et al., 2013. Contacting mechanical impedance of human finger based on uncertain system. IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics, p.1619–1624. [doi:10.1109/AIM.2013.6584328]Google Scholar
  3. Fang, H.G., Xie, Z.W., Liu, H., et al., 2009. An exoskeleton force feedback master finger distinguishing contact and non-contact mode. IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics, p.1059–1064. [doi:10.1109/AIM.2009.5229726]Google Scholar
  4. Hogan, N., 1985. Impedance control: an approach to manipulation: part I-theory. J. Dynam. Syst. Meas. Contr., 107(1):1–7.MATHCrossRefGoogle Scholar
  5. Huo, W.G., Huang, J., Wang, Y.J., et al., 2011. Control of upper-limb power-assist exoskeleton based on motion intention recognition. Int. Conf. on Robotics and Automation, p.2243–2248. [doi:10.1109/ICRA.2011.5980483]Google Scholar
  6. Kamal, H.S., Hamid, M., Farrokh, J.S., 2010. Model reference adaptive control design for a teleoperation system with output prediction. J. Intell. Robot. Syst., 59:319–339. [doi:10.1007/s10846-010-9400-4]MATHCrossRefGoogle Scholar
  7. Kamnik, R., Matko, D., Bajd, T., 1998. Application of model reference adaptive control to industrial robot impedance control. J. Intell. Robot. Syst., 22:153–163. [doi:10.1023/A:1007932701318]MATHCrossRefGoogle Scholar
  8. Kiguchi, K., Hayashi, Y., 2012. An EMG-based control for an upper-limb power-assist exoskeleton robot. IEEE Trans. Syst. Man. Cybern. B, 42:1064–1071. [doi:10.1109/TSMCB.2012.2185843]CrossRefGoogle Scholar
  9. Nakagawara, S., Kajimoto, H., Kawakami, N., et al., 2005. An encounter-type multi-fingered master hand using circuitous joints. Proc. IEEE Int. Conf. on Robotics and Automation, p.2667–2672. [doi:10.1109/ROBOT.2005.1570516]Google Scholar
  10. Nicosia, S., Tomei, P., 1984. Model reference adaptive control algorithms for industrial robots. Automatica, 20(5): 635–644. [doi:10.1016/0005-1098(84)90013-X]MATHCrossRefGoogle Scholar
  11. Pang, Z.H., Chui, H., 2009. System Identification and Adaptive Control. Beijing University of Aeronautics and Astronautics Press, Beijing, p.78–80 (in Chinese).Google Scholar
  12. Polotto, A., Modulo, F., Flumian, F., et al., 2012. Index finger rehabilitation/assistive device. 4th IEEE RAS/EMBS Int. Conf. on Biomedical Robotics and Biomechatronics, p.1518–1523. [doi:10.1109/BioRob.2012.6290676]Google Scholar
  13. Prange, G.B., Jannink M.J.A., Groothuis-Oudshoorn, C.G.M., et al., 2006. Systematic review of the effect of robotaided therapy on recovery of the hemiparetic arm after stroke. J. Rehabil. Res. Devel., 43(2):171–183. [doi:10.1682/JRRD.2005.04.0076]CrossRefGoogle Scholar
  14. Schabowsky, C.N., Godfrey, S.B., Holley, R.J., et al., 2010. Development and pilot testing of HEXORR: Hand EXOskeleton Rehabilitation Robot. J. NeuroEng. Rehabil., 7:36. [doi:10.1186/1743-0003-7-36]CrossRefGoogle Scholar
  15. Seraji, H., Colbaugh, R., 1997. Force tracking in impedance control. Int. J. Robot. Res., 16(1):97–117. [doi:10.1177/027836499701600107]CrossRefGoogle Scholar
  16. Takahashi, C.D., Der-Yeghiaian, L., Le, V., et al., 2008. Robot-based handmotor therapy after stroke. Brain, 131(2):425–437. [doi:10.1093/brain/awm311]CrossRefGoogle Scholar
  17. Tjahyono, A.P., Aw, K.C., Devaraj, H., et al., 2013. A fivefingered hand exoskeleton driven by pneumatic artificial muscles with novel polypyrrole sensors. Ind. Robot Int. J., 40(3):251–260. [doi:10.1108/01439911311309951]CrossRefGoogle Scholar
  18. Ueki, S., Kawasakia, H., Itoa, S., et al., 2012. Development of a hand-assist robot with multi-degrees-of-freedom for rehabilitation therapy. IEEE/ASME Trans. Mechatron., 17(1):136–146. [doi:10.1109/TMECH.2010.2090353]CrossRefGoogle Scholar
  19. Wege, A., Kondak, K., Hommel, G., 2006. Force control strategy or a hand exoskeleton based on sliding mode position control. Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, p.4615–4620. [doi:10.1109/IROS.2006.282169]Google Scholar

Copyright information

© Journal of Zhejiang University Science Editorial Office and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.State Key Laboratory of Fluid Power Transmission and ControlZhejiang UniversityHangzhouChina

Personalised recommendations