Adaptive control with a fuzzy tuner for cable-based rehabilitation robot

Yang, Jiankai; Su, Hang; Li, Zhijun; Ao, Di; Song, Rong

doi:10.1007/s12555-015-0049-4

Cited by 54 publications

(29 citation statements)

References 35 publications

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“…Then, we used the predefined fuzzy rule set (Table 1) to elaborate the relationship between the inputs and the outputs of the membership degree value. Finally, the center of the area was implemented as a defuzzification process to transform the membership degree values of the control signal to the actual value of the output u out1 (34). The u out1 was transmitted to the microcontroller to control the degree of the PWM wave.…”

Section: Methodsmentioning

confidence: 99%

Intensity- and Duration-Adaptive Functional Electrical Stimulation Using Fuzzy Logic Control and a Linear Model for Dropfoot Correction

et al. 2018

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Functional electrical stimulation (FES) is important in gait rehabilitation for patients with dropfoot. Since there are time-varying velocities during FES-assisted walking, it is difficult to achieve a good movement performance during walking. To account for the time-varying walking velocities, seven poststroke subjects were recruited and fuzzy logic control and a linear model were applied in FES-assisted walking to enable intensity- and duration-adaptive stimulation (IDAS) for poststroke subjects with dropfoot. In this study, the performance of IDAS was evaluated using kinematic data, and was compared with the performance under no stimulation (NS), FES-assisted walking triggered by heel-off stimulation (HOS), and speed-adaptive stimulation. A larger maximum ankle dorsiflexion angle in the IDAS condition than those in other conditions was observed. The ankle plantar flexion angle in the IDAS condition was similar to that of normal walking. Improvement in the maximum ankle dorsiflexion and plantar flexion angles in the IDAS condition could be attributed to having the appropriate stimulation intensity and duration. In summary, the intensity- and duration-adaptive controller can attain better movement performance and may have great potential in future clinical applications.

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Section: Methodsmentioning

confidence: 99%

Intensity- and Duration-Adaptive Functional Electrical Stimulation Using Fuzzy Logic Control and a Linear Model for Dropfoot Correction

et al. 2018

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“…Each country in the world has different degrees of industrialization and attention to industrial design, which indirectly affects the research level of applying TRIZ to industrial design. There are few international applied types of research on how to apply TRIZ to the product design processes in the industrial design field [19,20].…”

Section: Introductionmentioning

confidence: 99%

Neural Approximation Enhanced Predictive Tracking Control of a Novel Designed Four-Wheeled Rollator

Zhang

Fan

et al. 2019

Applied Sciences

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In the past few decades, the research of assistant mobile rollators for the elderly has attracted more and more investigation attention. In order to satisfy the needs of older people or disabled patients, this paper develops a neural approximation based predictive tracking control scheme to improve and support the handicapped through the novel four-wheeled rollator. Firstly, considering the industrial product theory, a novel Kano-TRIZ-QFD engineering design approach is presented to optimize the mechanical structure combined with humanistic care. At the same time, in order to achieve a stable trajectory tracking control for the assistant rollator system, a neural approximation enhanced predictive tracking control is discussed. Finally, autonomous tracking mobility of the presented control scheme has received sufficient advantage performance in position and heading angle variations under the external uncertainties. As the market for the medical device of the elderly rollators continues to progress, the method discussed in this article will attract more investigation and industry concerns.

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“…3 However, intensive rehabilitation motion training based on the restoration theories of muscles and neuroscience assists in improving the function recovery and self-care ability of a patient in his/her daily life after the stroke. 4,5 Rehabilitation training robots have been developed with novel technologies to assist patients in function recovery. Currently, there is an increasing interest to develop and apply robotic systems because robot-aided rehabilitation has demonstrated various advantages such as high precision, controllability, and high efficiency.…”

Section: Introductionmentioning

confidence: 99%

Study on motion performance of robot-aided passive rehabilitation exercises using novel dynamic motion planning strategy

Pan

Song

Duan

et al. 2019

International Journal of Advanced Robotic Systems

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The motion rehabilitation training robot is developed to help patients with motion dysfunction recover their motor function by providing a large amount of repetitive robot-aided exercise. To achieve stable and smooth robot-aided exercises for stroke patients, a motion control method with a novel dynamic motion planning strategy is proposed. The physical state of the training limb is assessed real time during the rehabilitation exercises. The dynamic motion planning strategy is developed by employing a suitable interpolation method dynamically corresponding to the physical state of the training limb to plan a trajectory tracking system that completely utilizes different interpolation characteristics to manage the movement in accordance with the time-varying physical state of the training limb. Concurrently, a position-based impedance control is adopted to achieve compliant movement. Functional (quantitative and qualitative) and clinical experiments are conducted on a four-degree-of-freedom whole-arm manipulator upper limb rehabilitation robot to verify the effectiveness of the control method designed with the dynamic motion planning strategy. The results indicate that the proposed control strategy can exhibit better performances in terms of the stability and smoothness.

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Adaptive control with a fuzzy tuner for cable-based rehabilitation robot

Cited by 54 publications

References 35 publications

Intensity- and Duration-Adaptive Functional Electrical Stimulation Using Fuzzy Logic Control and a Linear Model for Dropfoot Correction

Intensity- and Duration-Adaptive Functional Electrical Stimulation Using Fuzzy Logic Control and a Linear Model for Dropfoot Correction

Neural Approximation Enhanced Predictive Tracking Control of a Novel Designed Four-Wheeled Rollator

Study on motion performance of robot-aided passive rehabilitation exercises using novel dynamic motion planning strategy

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