Self-Learning Control of PMA-Actuated Knee-Joint Rehabilitation Training Device Based on Fuzzy Neural Network

Abstract:

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To solve the problem of the delay, nonlinearity and time-varying properties of PMA-actuated knee-joint rehabilitation training device, a self-learning control method based on fuzzy neural network is proposed in this paper. A self-learning controller was designed based on the combination of pid controller, feedforward controller, fuzzy neural network controller, and learning mechanism. It was applied to the isokinetic continuous passive motion control of the PMA-actuated knee-joint rehabilitation training device. The experiments proved that the self-learning controller has the properties of high control accuracy and unti-disturbance capability, comparing with pid controller. This control method provides the beneficial reference for improving the control performance of such system.

Info:

Periodical:

Key Engineering Materials (Volumes 467-469)

Edited by:

Dehuai Zeng

Pages:

1645-1650

DOI:

10.4028/www.scientific.net/KEM.467-469.1645

Citation:

X. Li et al., "Self-Learning Control of PMA-Actuated Knee-Joint Rehabilitation Training Device Based on Fuzzy Neural Network", Key Engineering Materials, Vols. 467-469, pp. 1645-1650, 2011

Online since:

February 2011

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Price:

$38.00

[1] T. Noritsugu, T. Tanaka: IEEE/ASME Transactions on Mechatronics, Vol. 2(4) (1997), p.259–267.

[2] Xiao Liangzi, Han Jian hai, Zhao Shushang, Sun Wei: Hydraulics and Pneumatics, (6) (2007), pp.64-66.

[3] E.J. Koeneman, R.S. Schultz, S.L. Wolf, in: Proceedings of the 26th Annual International Conference of the IEEE EMBS, San Francisco, CA, USA, (2004), pp.2711-2713.

[4] Tiffany Kline, Derek Kamper, Brian Schmit, in: Proceedings of the 2005 IEEE 9th International Conference on Rehabilitation Robotics, Chicago, IL, USA, (2005), pp.78-81.

[5] R.J. Sanchez, E. Wolbrecht, R. Smith, in: Proceedings of the 2005 IEEE 9th International Conference on Rehabilitation Robotics, Chicago, IL, USA, (2005), pp.500-504.

[6] Jiping He, E.J. Koeneman, R.S. Schultz, in: Proceedings of the 2005 IEEE 9th International Conference on Rehabilitation Robotics, Chicago, IL, USA, (2005), pp.95-98.

[7] Daisuke Sasaki, Toshiro Noritsugu, Masahiro Takaiwa, in: Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, (2005), pp.520-525.

[8] Hiroshi Kobayashi, Hidetoshi Suzuki, in: IEEE Workshop on Advanced Robotics and its Social Impacts, (2005), pp.149-154.

[9] Song Youlian: Journal of Shanghai DianJi University, Vol. 9(5) (2006), pp.5-9.

[10] Wu Yi: Modern Rehabilitation, 4(1) (2000), pp.8-10.

[11] Chan SW, John HL, Daniel WR, James EB, in: Proceedings of the 2003 IEEE international conference on fuzzy systems, (2003), p.278–283.

[12] Hesselroth T, Sarkar K, Van Der Smagt P, Schulten K: IEEE Trans Syst, 24(1) (1994), pp.28-38.

DOI: 10.1109/21.259683

[13] Kishore B, Kuldip SR, in: Proceedings of the 2003 IEEE international conference, (2003), p.432–436.

[14] Iskarous M, Kawamura K, in: Proceedings of the 1995 IEEE international conference, (1995), p.350–355.

[15] X. Li, H. He, S.C. Zhou: J. of Shenyang Polytechnic University, Vol. 20(6) (1998), pp.22-25.

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