An Impedance Control Method of Lower Limb Exoskeleton Rehabilitation Robot Based on Predicted Forward Dynamics

Wang, Yuefei; Liu, Zhen; Zhu, Liucun; Li, Xiaoying; Wang, Huaibin

doi:10.1109/trustcom50675.2020.00206

Cited by 13 publications

(4 citation statements)

References 3 publications

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“…Fuzzy SMC is used for motion control in [19][20][21][22][27][28][29]. Fuzzy logic is used for impedance control in [20,26,30] and for admittance control in [21,29]. Impedance control uses the ratio of position and force to control the force output by the system, while admittance control uses this ratio to control the position output.…”

Section: B Fuzzy Logic Controlmentioning

confidence: 99%

Effectiveness of Intelligent Control Strategies in Robot-Assisted Rehabilitation—A Systematic Review

Felix Brown,

Quan Xie

2024

IEEE Trans. Neural Syst. Rehabil. Eng.

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This review aims to provide a systematic analysis of the literature focused on the use of intelligent control systems in robotics for physical rehabilitation, identifying trends in recent research and comparing the effectiveness of intelligence used in control, with the aim of determining important factors in robotassisted rehabilitation and how intelligent controller design can improve them. Seven electronic research databases were searched for articles published in the years 2015 -2022 with articles selected based on relevance to the subject area of intelligent control systems in rehabilitation robotics. It was found that the most common use of intelligent algorithms for control is improving traditional control strategies with optimization and learning techniques. Intelligent algorithms are also commonly used in sensor output mapping, model construction, and for various data learning purposes. Experimental results show that intelligent controllers consistently outperform non-intelligent controllers in terms of transparency, tracking accuracy, and adaptability. Active participation of the patients and lowered interaction forces are consistently mentioned as important factors in improving the rehabilitation outcome as well as the patient experience. However, there are limited examples of studies presenting experimental results with impaired participants suffering limited range of motion, so the effectiveness of therapy provided by these systems is often difficult to quantify. A lack of universal evaluation criteria also makes it difficult to compare control systems outside of articles which use their own comparison criteria.

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Section: B Fuzzy Logic Controlmentioning

confidence: 99%

Effectiveness of Intelligent Control Strategies in Robot-Assisted Rehabilitation—A Systematic Review

Felix Brown,

Quan Xie

2024

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…Its unilateral leg has a total of 3 degrees of freedom, including two active degrees of freedom at hip joint and knee joint and one passive degree of freedom at ankle joint. The active DOF of knee joint and hip joint is driven by double bowden cable system [7]. The control system of the lower limb exoskeleton robot consists of six parts: main control module, driving module, power module, data transmission module, upper computer software and sensor detection module.…”

Section: Bowden Cable Driven Lower Limb Exoskeleton Systemmentioning

confidence: 99%

“…After integrating and simplifying the above formula, the tension of the bowden cable a and bowden cable b can be obtained to satisfy the relationship: (7) Among them，， .…”

Section: Double Bowden Cable Transmission Systemmentioning

confidence: 99%

Design of Human-Machine Collaborative Control Algorithm for Lower Limb Exoskeleton

2022

Proceedings of WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications

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In order to improve the flexibility and coordination of the exoskeleton robot, aiming at the problems of lower limb exoskeleton's poor adaptability to the external environment and poor humanmachine interaction, the human-machine interaction control technology of the lower limb exoskeleton system driven by flexible bowden cable is studied in this paper. Modeling the dynamics model of the lower limb exoskeleton system driven by double bowden cable, a neural network is used to identify the wearer's movement intentions on the basis of real-time control platform, and an adaptive impedance control strategy is designed to realize the human-machine dynamic coordination. The trajectory following of the exoskeleton is implemented by torque control, and the experiments of assisted walking at different speeds prove that the lower limb exoskeleton has good dynamic adjustment performance and can realize human-machine collaboration well. The evaluation experiment of the exoskeleton's auxiliary effect is carried out, and the EMG signals prove that the human-machine collaborative control algorithm has an auxiliary effect of 5.74%-9.73%.

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“…And the hybrid force/position control requires real-time detection of force and position changes, so many sensors need to be installed. Impedance control has been widely used to realize compliance control by adjusting the dynamic relationship between the human-machine position and the interacting force [15][16][17][18]. The Ekso lower limb exoskeleton used an impedance control strategy based on a force field controller, which firstly sets the desired motion trajectory and then corrects the gait trajectory by detecting the interactive forces between the human and the machine [15].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy radial-based impedance controller design for lower limb exoskeleton robot

Zhang

Elsabbagh

2022

Robotica

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The lower extremity rehabilitation exoskeleton is mainly used to help patients with movement disorders complete rehabilitation training. For the human-machine interaction problem of the lower limb rehabilitation exoskeleton, a fuzzy radial-based impedance (RBF-FVI) controller is proposed in this study. A six degree of freedom (DOF) lower extremity rehabilitation exoskeleton was developed, and the human-machine coupling dynamics model was established. To realize the compliance control of the human-machine coupling system, a novel RBF-FVI controller is designed, which includes an inner-loop fuzzy position control module and an outer-loop impedance control module. The inner-loop fuzzy position control module is mainly used to achieve the tracking control of the desired training trajectory and position adjustment amount. The outer-loop impedance control module regulates the impedance parameters and compensates for the uncertainty terms. The superiority of the proposed controller in trajectory following is verified through simulation and comparison tests. The hardware test of the human-machine coupling system was carried out, and the test results showed that the subject and the exoskeleton system could realize a coordinated and smooth movement.

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An Impedance Control Method of Lower Limb Exoskeleton Rehabilitation Robot Based on Predicted Forward Dynamics

Cited by 13 publications

References 3 publications

Effectiveness of Intelligent Control Strategies in Robot-Assisted Rehabilitation—A Systematic Review

Effectiveness of Intelligent Control Strategies in Robot-Assisted Rehabilitation—A Systematic Review

Design of Human-Machine Collaborative Control Algorithm for Lower Limb Exoskeleton

Fuzzy radial-based impedance controller design for lower limb exoskeleton robot

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