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Data-Driven Predictive Control of a Pneumatic Ankle Foot OrthosisULKIR, O. , AKGUN, G. , NASAB, A. , KAPLANOGLU, E.
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rehabilitation assistance, ankle-foot orthosis, subspace identification, PID, data-driven predictive control
foot(25), control(25), ankle(23), orthosis(22), design(12), systems(10), rehabilitation(8), predictive(7), active(7), driven(6)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2021-02-28
Volume 21, Issue 1, Year 2021, On page(s): 65 - 74
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.01007
Web of Science Accession Number: 000624018800007
SCOPUS ID: 85102782699
We present the design and control of a pneumatic ankle-foot orthosis (P-AFO) device powered via bi-directional pneumatic rotary actuator and a pneumatic artificial muscle for rehabilitation assistance and treatment of neuromuscular disorders. The rotary actuator and the pneumatic muscle assist with dorsiflexion and plantar flexion, respectively. The prototype is also equipped with simple sensor system for gait pattern analysis. The P-AFO has the capability of 20 degrees dorsiflexion from the plantar flexion and 12 degrees dorsiflexion from the neutral position of an ankle joint. The data-driven predictive control (DDPC) algorithm has been designed for P-AFO to follow desired gait cycle trajectories while rectifying the nonlinearity and uncertainties of the pneumatic actuators. The design of DDPC is realized from the subspace identification matrices acquired by the input-output values obtained as a result of an open-loop operation. The control structure is completely data-based without certain use of a model in the control implementation. In order to control the developed P-AFO prototype device, the suggested controller was implemented in a real-time operating system. Experimental studies are performed to compare the proposed controller with a three-term controller (PID) in trajectory tracking of the P-AFO.
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 Multi-Terrains Assistive Force Parameter Optimization Method for Soft Exoskeleton, Sun, Lei, Jing, Jiahui, Li, Chenghui, Lu, Rundong, IEEE Transactions on Neural Systems and Rehabilitation Engineering, ISSN 1534-4320, Issue , 2023.
Digital Object Identifier: 10.1109/TNSRE.2023.3267062 [CrossRef]
 Model predictive control of an active ankle-foot orthosis with non-linear actuation constraints, DeBoer, Benjamin, Hosseini, Ali, Rossa, Carlos, Control Engineering Practice, ISSN 0967-0661, Issue , 2023.
Digital Object Identifier: 10.1016/j.conengprac.2023.105538 [CrossRef]
 Data-Driven Predictive Control of Exoskeleton for Hand Rehabilitation with Subspace Identification, Kaplanoglu, Erkan, Akgun, Gazi, Sensors, ISSN 1424-8220, Issue 19, Volume 22, 2022.
Digital Object Identifier: 10.3390/s22197645 [CrossRef]
 Lower-Limb Robotic Assistance Devices for Drop Foot: A Review, Al-Rahmani, Nour, Mohan, Dhanya Menoth, Awad, Mohammad I., Wasti, Sabahat Asim, Hussain, Irfan, Khalaf, Kinda, IEEE Access, ISSN 2169-3536, Issue , 2022.
Digital Object Identifier: 10.1109/ACCESS.2022.3174686 [CrossRef]
 Optimal Finite- Time Prescribed Performance of Servo Pneumatic Positioning with PID Control Tuning using an Evolutionary Mating Algorithm, Irawan, Addie, Sulaiman, Mohd Herwan, Azahar, Mohd Iskandar Putra, 2023 IEEE 13th International Conference on Control System, Computing and Engineering (ICCSCE), ISBN 979-8-3503-2318-4, 2023.
Digital Object Identifier: 10.1109/ICCSCE58721.2023.10237170 [CrossRef]
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Stefan cel Mare University of Suceava, Romania
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