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Predictor-based tracking for neuromuscular electrical stimulation

delete2014-07-18
delete40
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OA
AI
I
Iasson Karafyllis
M
Michael Malisoff *
M
Marcio de Queiroz
M
Miroslav Krstić
R
Ruzhou Yang
DOI:10.1002/rnc.3211delete
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摘要

摘要

En 中文
We present a new tracking controller for neuromuscular electrical stimulation (NMES), which is an emerging technology that artificially stimulates skeletal muscles to help restore functionality to human limbs. The novelty of our work is that we prove that the tracking error globally asymptotically and locally exponentially converges to zero for any positive input delay, coupled with our ability to satisfy a state constraint imposed by the physical system. Also, our controller only requires sampled measurements of the states instead of continuous measurements and allows perturbed sampling schedules, which can be important for practical purposes. Our work is based on a new method for constructing predictor maps for a large class of time-varying systems, which is of independent interest. Copyright (c) 2014 John Wiley & Sons, Ltd.
Keyword:
nonlinear systems
delay systems
NMES models
numerical methods

期刊

International Journal of Robust and Nonlinear Control 封面图
International Journal of Robust and Nonlinear Control
IF:
3.2
论文数:
7.0K
被引数:
1.4W

机构

L
louisiana state university system
学者数:
2.3W
论文数: 2.0W
被引数: 15
N
National Technical University of Athens
学者数:
9.7K
论文数: 9.5K
被引数: 8.2K
L
Louisiana State University
学者数:
9.8K
论文数: 8.0K
被引数: 1.6W
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