Exoskeleton Hand Control by Fractional Order Models

Ivănescu, Mircea; Popescu, Nirvana; Popescu, Decebal; Channa, Asma; Poboroniuc, Marian

doi:10.3390/s19214608

Cited by 12 publications

(5 citation statements)

References 27 publications

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“…Figure 1 shows the architecture of such a system that represents a complex structure of muscle tissues combined with elements of mechanical structure. An advanced conceptual analysis of the dynamics of these systems indicates the use of fractional calculus in Maxwell's classic stress-strain models [41,42].…”

Section: Soft Exoskeleton Glove Controlmentioning

confidence: 99%

Control Techniques for a Class of Fractional Order Systems

et al. 2021

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The paper discusses several control techniques for a class of systems described by fractional order equations. The paper presents the unit frequency criteria that ensure the closed loop control for: Fractional Order Linear Systems, Fractional Order Linear Systems with nonlinear components, Time Delay Fractional Order Linear Systems, Time Delay Fractional Order Linear Systems with nonlinear components. The stability criterion is proposed for the systems composed of fractional order subsystems. These techniques are used in two applications: Soft Exoskeleton Glove Control, studied as a nonlinear model with time delay and Disabled Man-Wheelchair model, analysed as a fractional-order multi-system.

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Section: Soft Exoskeleton Glove Controlmentioning

confidence: 99%

Control Techniques for a Class of Fractional Order Systems

et al. 2021

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“…The intelligent haptic robot-glove (IHRG), for the monitoring or control of human behavior, is well described by the fractional order model (FOM) operators for the rehabilitation of patients that have a diagnosis of a cerebrovascular accident [ 5 ]. An exoskeleton architecture ensures the mechanical compliance of human fingers.…”

Section: Review Of the Contributions In This Special Issuementioning

confidence: 99%

Advanced Intelligent Control through Versatile Intelligent Portable Platforms

Vlădăreanu

2020

Sensors

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Deep research and communicating new trends in the design, control and applications of the real time control of intelligent sensors systems using advanced intelligent control methods and techniques is the main purpose of this research. The innovative multi-sensor fusion techniques, integrated through the Versatile Intelligent Portable (VIP) platforms are developed, combined with computer vision, virtual and augmented reality (VR&AR) and intelligent communication, including remote control, adaptive sensor networks, human-robot (H2R) interaction systems and machine-to-machine (M2M) interfaces. Intelligent decision support systems (IDSS), including remote sensing, and their integration with DSS, GA-based DSS, fuzzy sets DSS, rough sets-based DSS, intelligent agent-assisted DSS, process mining integration into decision support, adaptive DSS, computer vision based DSS, sensory and robotic DSS, are highlighted in the field of advanced intelligent control.

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“…By moving the remote host to a more convenient position, maintaining a rigid structure, or combined with a flexible fabric structure, this method frees the remote from the heavy driving unit and electronic equipment, thus increasing the portability, comfort, and usability of the equipment [22][23][24][25]. Although the development of this drive system aims to improve usability, reduce weight, and maximize compliance, the inevitable cost is the decrease in strength and accuracy compared with the traditional rigid exoskeleton [26][27][28][29]. As shown in Figure 1a, Dario Marconi designed a new index finger-thumb exoskeleton named HX-β for hand rehabilitation by lasso transmission, which allowed the thumb to flex/extend and rotate independently, thus realizing various natural and functional grasping configurations [30].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Analysis and Experimental Study of Lasso Transmission for Hand Rehabilitation Robot

Guo

Yang

2023

Micromachines

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Lasso transmission is a method for realizing long-distance flexible transmission and lightweight robots. However, there are transmission characteristic losses of velocity, force, and displacement during the motion of lasso transmission. Therefore, the analysis of transmission characteristic losses of lasso transmission has become the focus of research. For this study, at first, we developed a new flexible hand rehabilitation robot with a lasso transmission method. Second, the theoretical analysis and simulation analysis of the dynamics of the lasso transmission in the flexible hand rehabilitation robot were carried out to calculate the force, velocity, and displacement losses of the lasso transmission. Finally, the mechanism and transmission models were established for experimental studies to measure the effects of different curvatures and speeds on the lasso transmission torque. The experimental data and image analysis results show torque loss in the process of lasso transmission and an increase in torque loss with the increase in the lasso curvature radius and transmission speed. The study of the lasso transmission characteristics is important for the design and control of hand functional rehabilitation robots, providing an important reference for the design of flexible rehabilitation robots and also guiding the research on the lasso regarding the compensation method for transmission losses.

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Exoskeleton Hand Control by Fractional Order Models

Cited by 12 publications

References 27 publications

Control Techniques for a Class of Fractional Order Systems

Control Techniques for a Class of Fractional Order Systems

Advanced Intelligent Control through Versatile Intelligent Portable Platforms

Dynamic Analysis and Experimental Study of Lasso Transmission for Hand Rehabilitation Robot

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