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Design, modelling and identification of a fiber-reinforced bending pneumatic muscle

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References

  1. Peng L, Hou Z G, Peng L, et al. Robot assisted rehabilitation of the arm after stroke: prototype design and clinical evaluation. Sci China Inf Sci, 2017, 60: 073201

    Article  Google Scholar 

  2. Huang J, Qian J, Liu L, et al. Echo state network based predictive control with particle swarm optimization for pneumatic muscle actuator. J Franklin Inst, 2016, 353: 2761–2782

    Article  MathSciNet  MATH  Google Scholar 

  3. Al-Fahaam H, Davis S, Nefti-Meziani S. Power assistive and rehabilitation wearable robot based on pneumatic soft actuators. In: Proceedings of the 21st International Conference on Methods and Models in Automation and Robotics (MMAR), 2016. 472–477

    Google Scholar 

  4. Zhao H C, Jalving J, Huang R K, et al. A helping hand: soft orthosis with integrated optical strain sensors and EMG control. IEEE Robot Autom Mag, 2016, 23: 55–64

    Article  Google Scholar 

  5. Guo Y, Kang R J, Chen L S. Dynamic modeling for a continuum robot with compliant structure. In: Proceedings of International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2015

    Book  Google Scholar 

  6. Polygerinos P, Wang Z, Overvelde J T B, et al. Modeling of soft fiber-reinforced bending actuators. IEEE Trans Robot, 2015, 31: 778–789

    Article  Google Scholar 

  7. Zhang L B, Bao G J, Yang Q H, et al. Static model of flexible pneumatic bending joint. In: Proceedings of International Conference on Control, Automation, Robotics and Vision, 2007

    Google Scholar 

  8. Ru H, Huang J, Xiong C, et al. Design and control of a soft bending pneumatic actuator based on visual feedback. In: Proceedings of the World Congress on Intelligent Control and Automation (WCICA), Changsha, 2018

    Book  Google Scholar 

  9. Reynolds D B, Repperger D W, Phillips C A, et al. Modeling the dynamic characteristics of pneumatic muscle. Ann BioMed Eng, 2003, 31: 310–317

    Article  Google Scholar 

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 61473130, 91648203, 51335004).

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Authors and Affiliations

  1. School of Automation, Huazhong University of Science and Technology, Wuhan, 430074, China

    Hongge Ru, Jian Huang, Junzhe Wang & Jun Huo

  2. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China

    Wenbin Chen & Caihua Xiong

Authors
  1. Hongge Ru
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  2. Jian Huang
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  3. Wenbin Chen
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  4. Caihua Xiong
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  5. Junzhe Wang
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  6. Jun Huo
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Corresponding author

Correspondence to Jian Huang.

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Ru, H., Huang, J., Chen, W. et al. Design, modelling and identification of a fiber-reinforced bending pneumatic muscle. Sci. China Inf. Sci. 62, 50213 (2019). https://doi.org/10.1007/s11432-018-9709-x

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  • DOI: https://doi.org/10.1007/s11432-018-9709-x

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