Neural-network-based nonlinear model predictive tracking control of a pneumatic muscle actuator-driven exoskeleton

Pneumatic muscle actuators &#x0028 PMAs &#x0029 are compliant and suitable for robotic devices that have been shown to be effective in assisting patients with neurologic injuries, such as strokes, spinal cord injuries, etc., to accomplish rehabilitation tasks. However, because PMAs have nonl...

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Vydané v:	IEEE/CAA journal of automatica sinica Ročník 7; číslo 6; s. 1478 - 1488
Hlavní autori:	Cao, Yu, Huang, Jian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway Chinese Association of Automation (CAA) 01.11.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Predmet:	Actuation Actuators Algorithms Approximation Control stability Control systems design Controllers Exoskeletons Feedback control Gait Gaussian process Gaussian processes Legged locomotion Mathematical analysis Muscles Neural networks Nonlinear control Optimization Orthoses Predictive control Predictive models Rehabilitation Spinal cord injuries Subsystems System dynamics Task complexity Tracking control Training model predictive control Echo state Gaussian process neural network pneumatic muscle actuators-driven exoskeleton
ISSN:	2329-9266, 2329-9274
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