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Applied Bionics and Biomechanics
Volume 2016 (2016), Article ID 5017381, 13 pages
http://dx.doi.org/10.1155/2016/5017381
Research Article

Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton

State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China

Received 16 January 2016; Accepted 17 February 2016

Academic Editor: Huapeng Wu

Copyright © 2016 Yi Long et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. H. Kazerooni, R. Steger, and L. Huang, “Hybrid control of the Berkeley Lower Extremity Exoskeleton (BLEEX),” International Journal of Robotics Research, vol. 25, no. 5-6, pp. 561–573, 2006. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Zoss, H. Kazerooni, and A. Chu, “On the mechanical design of the Berkeley Lower Extremity Exoskeleton (BLEEX),” in Proceedings of the IRS/RSJ International Conference on Intelligent Robots and Systems (IROS '05), pp. 3132–3139, August 2005. View at Publisher · View at Google Scholar · View at Scopus
  3. http://bleex.me.berkeley.edu/research/exoskeleton/hulc/.
  4. H. Kawamoto and Y. Sankai, “Power assist method based on Phase Sequence and muscle force condition for HAL,” Advanced Robotics, vol. 19, no. 7, pp. 717–734, 2005. View at Publisher · View at Google Scholar · View at Scopus
  5. A. Zelinsky, “Robot suit hybrid assistive limb,” IEEE Robotics and Automation Magazine, vol. 16, no. 4, pp. 98–102, 2009. View at Publisher · View at Google Scholar · View at Scopus
  6. S. Maeshima, A. Osawa, D. Nishio et al., “Efficacy of a hybrid assistive limb in post-stroke hemiplegic patients: a preliminary report,” BMC Neurology, vol. 11, no. 1, article 116, 6 pages, 2011. View at Google Scholar
  7. S. Yu, C. Han, and I. Cho, “Design considerations of a lower limb exoskeleton system to assist walking and load-carrying of infantry soldiers,” Applied Bionics & Biomechanics, vol. 11, no. 3, pp. 119–134, 2014. View at Publisher · View at Google Scholar · View at Scopus
  8. J. C. Moreno, F. Brunetti, E. Navarro, A. Forner-Cordero, and J. L. Pons, “Analysis of the human interaction with a wearable lower-limb exoskeleton,” Applied Bionics & Biomechanics, vol. 6, no. 2, pp. 245–256, 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. M. H. Rahman, M. Saad, J.-P. Kenné, and P. S. Archambault, “Control of an exoskeleton robot arm with sliding mode exponential reaching law,” International Journal of Control, Automation and Systems, vol. 11, no. 1, pp. 92–104, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. X. T. Tran and H. J. Kang, “Adaptive hybrid high-order terminal sliding mode control of MIMO uncertain nonlinear systems and its application to robot manipulators,” International Journal of Precision Engineering and Manufacturing, vol. 16, no. 2, pp. 255–266, 2015. View at Publisher · View at Google Scholar
  11. T. Hsiao and M.-C. Weng, “Robust joint position feedback control of robot manipulators,” Journal of Dynamic Systems, Measurement and Control, vol. 135, no. 3, Article ID 031010, pp. 815–826, 2013. View at Publisher · View at Google Scholar · View at Scopus
  12. H. G. Sage, M. F. de Mathelin, and E. Ostertag, “Robust control of robot manipulators: a survey,” International Journal of Control, vol. 72, no. 16, pp. 1498–1522, 1999. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  13. H. C. Cho, M. S. Fadali, K. S. Lee, and N. H. Kim, “Adaptive position and trajectory control of autonomous mobile robot systems with random friction,” IET Control Theory & Applications, vol. 4, no. 12, pp. 2733–2742, 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. S. A. M. Dehghan, M. Danesh, and F. Sheikholeslam, “Adaptive hybrid force/position control of robot manipulators using an adaptive force estimator in the presence of parametric uncertainty,” Advanced Robotics, vol. 29, no. 4, pp. 209–223, 2015. View at Publisher · View at Google Scholar
  15. R.-J. Wai, Y.-C. Huang, Z.-W. Yang, and C.-Y. Shih, “Adaptive fuzzy-neural-network velocity sensorless control for robot manipulator position tracking,” IET Control Theory & Applications, vol. 4, no. 6, pp. 1079–1093, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. J. Y. Cheong, S. I. Han, and J. M. Lee, “Adaptive fuzzy dynamic surface sliding mode position control for a robot manipulator with friction and deadzone,” Mathematical Problems in Engineering, vol. 2013, Article ID 161325, 15 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  17. V. Utkin, J. Guldner, and J. Shi, Sliding Mode Control in Electro-mechanical Systems, CRC Press, New York, NY, USA, 2009.
  18. F. G. Rossomando, C. Soria, and R. Carelli, “Sliding mode neuro adaptive control in trajectory tracking for mobile robots,” Journal of Intelligent & Robotic Systems, vol. 74, no. 3-4, pp. 931–944, 2014. View at Publisher · View at Google Scholar · View at Scopus
  19. M. Taherkhorsandi, M. J. Mahmoodabadi, M. Talebipour, and K. K. Castillo-Villar, “Pareto design of an adaptive robust hybrid of PID and sliding control for a biped robot via genetic algorithm optimization,” Nonlinear Dynamics, vol. 79, no. 1, pp. 251–263, 2014. View at Publisher · View at Google Scholar · View at Scopus
  20. B. S. K. K. Ibrahim, R. Ngadengon, and M. N. Ahmad, “Genetic algorithm optimized integral sliding mode control of a direct drive robot arm,” in Proceedings of the International Conference on Control, Automation and Information Sciences (ICCAIS '12), pp. 328–333, Ho Chi Minh City, Vietnam, November 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. M. R. Soltanpour and M. H. Khooban, “A particle swarm optimization approach for fuzzy sliding mode control for tracking the robot manipulator,” Nonlinear Dynamics, vol. 74, no. 1-2, pp. 467–478, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  22. Y.-H. Chang, C.-W. Chang, C.-W. Tao, H.-W. Lin, and J.-S. Taur, “Fuzzy sliding-mode control for ball and beam system with fuzzy ant colony optimization,” Expert Systems with Applications, vol. 39, no. 3, pp. 3624–3633, 2012. View at Publisher · View at Google Scholar · View at Scopus
  23. C. Su, G. Lii, and H. Hwung, “Position control employing fuzzy-sliding mode and genetic algorithms with a modified evolutionary direction operator,” International Journal of Cybernetics & Systems, vol. 30, pp. 873–891, 2010. View at Google Scholar
  24. E. Fuchs and M. A. S. Masoum, Power Quality in Power Systems and Electrical Machines, Academic Press, New York, NY, USA, 2011.
  25. S. J. Got, M. C. Lee, and M. K. Park, “Fuzzy-sliding mode control of a polishing robot based on genetic algorithm,” Journal of Mechanical Science & Technology, vol. 15, pp. 580–591, 2001. View at Google Scholar
  26. M. J. Kharaajoo and H. Rouhani, Advances in Artificial Intelligence, Springer, Berlin, Germany, 2004.
  27. M. J. Mahmoodabadi, M. Taherkhorsandi, M. Talebipour, and K. K. Castillo-Villar, “Adaptive robust PID control subject to supervisory decoupled sliding mode control based upon genetic algorithm optimization,” Transactions of the Institute of Measurement & Control, vol. 37, no. 4, pp. 505–514, 2015. View at Publisher · View at Google Scholar
  28. A. R. Firdaus and A. S. Rahman, “Genetic algorithm of sliding mode control design for manipulator robot,” Telecommunication Computing Electronics and Control, vol. 10, pp. 645–654, 2012. View at Google Scholar
  29. J. S. Albus, “A new approach to manipulator control: the cerebellar model articulation controller (CMAC),” Journal of Dynamic Systems, Measurement, and Control, vol. 97, pp. 220–227, 1975. View at Google Scholar
  30. W. Yu, M. A. Moreno-Armendariz, and F. O. Rodriguez, “Stable adaptive compensation with fuzzy CMAC for an overhead crane,” Information Sciences, vol. 181, no. 21, pp. 4895–4907, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  31. H. Duan and D. Gu, “Sliding mode adaptive control for flying robot based on recurrent CMAC algorithm,” in Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA '11), pp. 440–445, Beijing, China, August 2011. View at Publisher · View at Google Scholar · View at Scopus
  32. A. Chu, Design of the Berkley lower extremity exoskeleton (BLEEX) [Ph.D. thesis], University of California, Berkeley, Calif, USA, 2005.
  33. C. Kirtley, CGA Normative Gait Database, http://www.clinicalgaitanalysis.com/data/.
  34. M. W. Spong, S. Hutchinson, and M. Vidyasagar, Robot Modeling and Control, John Wiley & Sons, New York, NY, USA, 2006.
  35. J.-H. Lee, “Highly robust position control of BLDDSM using an improved integral variable structure systems,” Automatica, vol. 42, no. 6, pp. 929–935, 2006. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  36. J. J. Slotine and W. Li, Applied Nonlinear Control, Prentice-Hall, Englewood Cliffs, NJ, USA, 1991.
  37. Y. Long and X.-J. Yang, “Robust adaptive fuzzy sliding mode synchronous control for a planar redundantly actuated parallel manipulator,” in Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO '12), pp. 2264–2269, Guangzhou, China, December 2012. View at Publisher · View at Google Scholar · View at Scopus
  38. M. Krstic, I. Kanellakopoulos, and P. V. Kokotovic, Nonlinear and Adaptive Control Design, John Wiley & Sons, New York, NY, USA, 1995.
  39. E. Köse, K. Abacı, H. Kızmaz, S. Aksoy, and M. A. Yalçin, “Sliding mode control based on genetic algorithm for WSCC systems include of SVC,” Electronics and Electrical Engineering, vol. 19, no. 4, pp. 25–28, 2013. View at Publisher · View at Google Scholar
  40. M. Mitchell, An Introduction to Genetic Algorithms, MIT Press, Cambridge, Mass, USA, 5th edition, 1999.
  41. G. Horváth, “Kernel CMAC: an efficient neural network for classification and regression,” Acta Polytechnica Hungarica, vol. 3, no. 1, pp. 5–20, 2006. View at Google Scholar · View at Scopus
  42. X. J. Yang and Y. Long, “Synchronous trajectory tracking control and simulation of CMAC neural network based on computed torque control,” Journal of Harbin Institute of Technology, vol. 45, no. 7, pp. 85–89, 2013. View at Google Scholar · View at Scopus
  43. W. T. Miller III, R. P. Hewes, F. H. Glanz, and L. G. Kraft, “Real-time dynamic control of an industrial manipulator using a neural network-based learning controller,” IEEE Transactions on Robotics and Automation, vol. 6, no. 1, pp. 1–9, 1990. View at Publisher · View at Google Scholar · View at Scopus
  44. F.-C. Chen and C.-H. Chang, “Practical stability issues in CMAC neural network control systems,” IEEE Transactions on Control Systems Technology, vol. 4, no. 1, pp. 86–91, 1996. View at Publisher · View at Google Scholar · View at Scopus
  45. K. Mohajeri, G. Pishehvar, and M. Seifi, “CMAC neural networks structures,” in Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA '09), pp. 39–45, Daejeon, Republic of Korea, December 2009. View at Publisher · View at Google Scholar · View at Scopus