Fuzzy and learning control of fes induced gait

T.J.A. de Vries; W.J.R. Velthuis; J. van Amerongen; P.H. Veltink

Fuzzy and learning control of fes induced gait

T.J.A. de Vries, W.J.R. Velthuis, J. van Amerongen, P.H. Veltink

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Research is done to restore gait by means of functional electrical stimulation for people suffering from paraplegia. Difficulties are that muscle fatigue and heavily changing patient conditions deteriorate the performance of such systems. The design of feedback controllers is considered that adapt stimulation parameters to compensate for this deterioration. Conventional control (PID) gives good performance when muscle and leg dynamics are known, but requires recurring identification. By using fuzzy controllers based on general, qualitative knowledge, and by providing self-tuning capabilities through learning, identification might be avoided. Simulation studies confirm this.

Original language	English
Title of host publication	Proceedings of the 13th World Congress International Federation of Automatic Control
Subtitle of host publication	San Francisco, USA, 30th June-5th July 1996
Place of Publication	New York, NY
Publisher	Pergamon
Pages	421-426
Number of pages	6
Volume	K
ISBN (Print)	9780080429199
Publication status	Published - 30 Jun 1996

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title = "Fuzzy and learning control of fes induced gait",

abstract = "Research is done to restore gait by means of functional electrical stimulation for people suffering from paraplegia. Difficulties are that muscle fatigue and heavily changing patient conditions deteriorate the performance of such systems. The design of feedback controllers is considered that adapt stimulation parameters to compensate for this deterioration. Conventional control (PID) gives good performance when muscle and leg dynamics are known, but requires recurring identification. By using fuzzy controllers based on general, qualitative knowledge, and by providing self-tuning capabilities through learning, identification might be avoided. Simulation studies confirm this. ",

author = "{de Vries}, T.J.A. and W.J.R. Velthuis and {van Amerongen}, J. and P.H. Veltink",

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Fuzzy and learning control of fes induced gait. / de Vries, T.J.A.; Velthuis, W.J.R.; van Amerongen, J. et al.
Proceedings of the 13th World Congress International Federation of Automatic Control: San Francisco, USA, 30th June-5th July 1996. Vol. K New York, NY: Pergamon, 1996. p. 421-426.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Fuzzy and learning control of fes induced gait

AU - de Vries, T.J.A.

AU - Velthuis, W.J.R.

AU - van Amerongen, J.

AU - Veltink, P.H.

PY - 1996/6/30

Y1 - 1996/6/30

N2 - Research is done to restore gait by means of functional electrical stimulation for people suffering from paraplegia. Difficulties are that muscle fatigue and heavily changing patient conditions deteriorate the performance of such systems. The design of feedback controllers is considered that adapt stimulation parameters to compensate for this deterioration. Conventional control (PID) gives good performance when muscle and leg dynamics are known, but requires recurring identification. By using fuzzy controllers based on general, qualitative knowledge, and by providing self-tuning capabilities through learning, identification might be avoided. Simulation studies confirm this.

AB - Research is done to restore gait by means of functional electrical stimulation for people suffering from paraplegia. Difficulties are that muscle fatigue and heavily changing patient conditions deteriorate the performance of such systems. The design of feedback controllers is considered that adapt stimulation parameters to compensate for this deterioration. Conventional control (PID) gives good performance when muscle and leg dynamics are known, but requires recurring identification. By using fuzzy controllers based on general, qualitative knowledge, and by providing self-tuning capabilities through learning, identification might be avoided. Simulation studies confirm this.

M3 - Conference contribution

SN - 9780080429199

VL - K

SP - 421

EP - 426

BT - Proceedings of the 13th World Congress International Federation of Automatic Control

PB - Pergamon

CY - New York, NY

ER -

Fuzzy and learning control of fes induced gait

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