Adaptive Servomechanism of Pneumatic Muscle Actuators With Uncertainties

Zhu, Lijun; Shi, Xianyi; Chen, Zhiyong; Zhang, Haitao; Chen, Xiong

doi:10.1109/tie.2016.2573266

Cited by 39 publications

(21 citation statements)

References 30 publications

(49 reference statements)

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“…Specifically, they can be modeled as a parallel connection of a nonlinear friction force, a nonlinear spring, and a nonlinear contractile element. It is difficult to identify the coefficients associated with these elements with precision, as they change along the course of continuous use [ 73 ]. Therefore, trajectory tracking control is of vital importance for pneumatic-driven PARRs.…”

Section: Resultsmentioning

confidence: 99%

State of the art in parallel ankle rehabilitation robot: a systematic review

Dong

Zhou

et al. 2021

J NeuroEngineering Rehabil

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Background The ankle joint complex (AJC) is of fundamental importance for balance, support, and propulsion. However, it is particularly susceptible to musculoskeletal and neurological injuries, especially neurological injuries such as drop foot following stroke. An important factor in ankle dysfunction is damage to the central nervous system (CNS). Correspondingly, the fundamental goal of rehabilitation training is to stimulate the reorganization and compensation of the CNS, and to promote the recovery of the motor system’s motor perception function. Therefore, an increasing number of ankle rehabilitation robots have been developed to provide long-term accurate and uniform rehabilitation training of the AJC, among which the parallel ankle rehabilitation robot (PARR) is the most studied. The aim of this study is to provide a systematic review of the state of the art in PARR technology, with consideration of the mechanism configurations, actuator types with different trajectory tracking control techniques, and rehabilitation training methods, thus facilitating the development of new and improved PARRs as a next step towards obtaining clinical proof of their rehabilitation benefits. Methods A literature search was conducted on PubMed, Scopus, IEEE Xplore, and Web of Science for articles related to the design and improvement of PARRs for ankle rehabilitation from each site’s respective inception from January 1999 to September 2020 using the keywords “ parallel”, “ ankle”, and “ robot”. Appropriate syntax using Boolean operators and wildcard symbols was utilized for each database to include a wider range of articles that may have used alternate spellings or synonyms, and the references listed in relevant publications were further screened according to the inclusion criteria and exclusion criteria. Results and discussion Ultimately, 65 articles representing 16 unique PARRs were selected for review, all of which have developed the prototypes with experiments designed to verify their usability and feasibility. From the comparison among these PARRs, we found that there are three main considerations for the mechanical design and mechanism optimization of PARRs, the choice of two actuator types including pneumatic and electrically driven control, the covering of the AJC’s motion space, and the optimization of the kinematic design, actuation design and structural design. The trajectory tracking accuracy and interactive control performance also need to be guaranteed to improve the effect of rehabilitation training and stimulate a patient’s active participation. In addition, the parameters of the reviewed 16 PARRs are summarized in detail with their differences compared by using figures and tables in the order they appeared, showing their differences in the two main actuator types, four exercise modes, fifteen control strategies, etc., which revealed the future research trends related to the improvement of the PARRs. Conclusion The selected studies showed the rapid development of PARRs in terms of their mechanical designs, control strategies, and rehabilitation training methods over the last two decades. However, the existing PARRs all have their own pros and cons, and few of the developed devices have been subjected to clinical trials. Designing a PARR with three degrees of freedom (DOFs) and whereby the mechanism’s rotation center coincides with the AJC rotation center is of vital importance in the mechanism design and optimization of PARRs. In addition, the design of actuators combining the advantages of the pneumatic-driven and electrically driven ones, as well as some new other actuators, will be a research hotspot for the development of PARRs. For the control strategy, compliance control with variable parameters should be further studied, with sEMG signal included to improve the real-time performance. Multimode rehabilitation training methods with multimodal motion intention recognition, real-time online detection and evaluation system should also be further developed to meet the needs of different ankle disability and rehabilitation stages. In addition, the clinical trials are in urgent need to help the PARRs be implementable as an intervention in clinical practice.

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Section: Resultsmentioning

confidence: 99%

State of the art in parallel ankle rehabilitation robot: a systematic review

Dong

Zhou

et al. 2021

J NeuroEngineering Rehabil

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“…In [9], a neural network based predictive control algorithms was developed for the trajectory tracking control of PAM sytems. In [10] and [11], a backstepping adaptive control controller was designed for PAM systems, respectively. In [12], the fuzzy control for pneumatic muscle driven rehabilitation robot was studied, and a modified genetic algorithm was developed to identify the optimal set of parameters for the fuzzy controller.…”

Section: Introductionmentioning

confidence: 99%

Angle Tracking Robust Learning Control for Pneumatic Artificial Muscle Systems

Guo¹,

Wang

Zhang

et al. 2021

IEEE Access

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Pneumatic artificial muscle systems have been widely used in the applications of biomimetic robots and medical auxiliary devices. The existence of high nonlinearities, uncertainties and time-varying characteristics in pneumatic artificial muscle systems brings much challenge for accurate system modeling and controller design. In this paper, a robust adaptive iterative learning control scheme is proposed to solve the angle tracking problem for a kind of pneumatic artificial muscle-actuated mechanism. After deriving the system model according to the feature of mechanism, Lyapunov synthesis method is used to design the control law and adaptive learning laws. Robust strategy and full saturation learning strategy are jointly used to compensate parametric/ nonparametric uncertainties and reject external disturbances. Alignment condition is applied to solve the initial position problem of iterative learning control. As the iteration number increases, the system state can accurately track the reference trajectory over the whole interval. In the end, a simulation example is presented to demonstrate the effectiveness of the designed control scheme.

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“…To this end, pneumatic-driven PARRs usually use pneumatic muscle actuators (PMAs) as actuators, which can provide an intrinsic softness to make joint compliance possible because of their superiority in terms of their low weight and high power/volume ratios (Meng et al , 2017; Liu et al , 2017). However, achieving precise control of PMAs is a challenging problem owing to their non-linear and time-varying characteristics (Zhu et al , 2017). On the other hand, electrically driven PARRs use electric motors as the actuators, which can achieve relatively high control accuracy, but the motors have no intrinsic compliance.…”

Section: Introductionmentioning

confidence: 99%

Implementation of passive compliance training on a parallel ankle rehabilitation robot to enhance safety

Fan

Dong

et al. 2020

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Purpose The purpose of this paper is to implement a passive compliance training strategy for our newly designed 2-UPS/RRR parallel ankle rehabilitation robot (PARR) to enhance its rehabilitation training safety. Design/methodology/approach First, a kinematic analysis of the PARR is introduced, and the mechanism ensures that the rotation centre of the ankle joint complex (AJC) coincides with robot’s rotation centre. Then, a passive compliance training strategy based on admittance control is described in detail and is implemented on our PARR. Findings Experiments involving healthy subjects were conducted, and the performance of trajectory tracking was quantitatively evaluated, with the results showing excellent compliance and trajectory tracking accuracy, which can ensure that a secondary injury to the AJC during passive rehabilitation training is avoided. The influence of different admittance parameters was also simulated and analysed, which can contribute to the development of adaptive parameter adjustment research. Originality/value The paper can be used to improve the effectiveness of ankle rehabilitation, to alleviate manual therapy problems in terms of labour intensiveness, precision and subjectivity and to ensure safety and comfort during rehabilitation sessions.

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Adaptive Servomechanism of Pneumatic Muscle Actuators With Uncertainties

Cited by 39 publications

References 30 publications

State of the art in parallel ankle rehabilitation robot: a systematic review

State of the art in parallel ankle rehabilitation robot: a systematic review

Angle Tracking Robust Learning Control for Pneumatic Artificial Muscle Systems

Implementation of passive compliance training on a parallel ankle rehabilitation robot to enhance safety

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