Skip to main content

Feasibility of Pi Control for a Double-Acting Cylinder Actuated by Mckibben Muscles

  • Conference paper
  • First Online:
RiTA 2020

Abstract

Pneumatic actuators are fast becoming a key instrument where cost, safety or pollution is a concern. They can be of linear or rotary type, depending on the motion they produce. Linear pneumatic actuator is also commonly known as pneumatic cylinder because it usually consists of a piston housed in a hollow cylinder. In this study, the feasibility of PID control for a double-acting cylinder actuated by McKibben muscles (DACAM) had been investigated. Due to the nonlinearity and hysteresis properties of the muscle, separate controllers for forward actuation and reverse actuation had been used. Result shows that when given a staircase input, the feedback system gave an average response of 4.28 s rise time, 6.06 s settling time, 0.01% overshoot and 0.01% steady-state error for forward actuation and 8.25 s fall time, 9.28 s settling time, 2.86% overshoot and 2.86% steady-state error for reverse actuation. The evidence from this study suggests that position control of a DACAM using PI control is possible. An implication of this is the possibility of developing a small, lightweight and simple pneumatic cylinder using McKibben muscles.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Daerden, F., Lefeber, D.: Pneumatic artificial muscles: actuators for robotics and automation. Eur. J. Mech. Environ. Eng. 47(1), 11–21 (2002)

    Google Scholar 

  2. Caldwell, D.G., Razak, A., Goodwin, M.: Braided pneumatic muscle actuators. IFAC Proc. Vol. 26(1), 522–527 (1993)

    Article  Google Scholar 

  3. Caldwell, D.G., Medrano-Cerda, G.A., Goodwin, M.: Control of pneumatic muscle actuators. IEEE Control Syst. 15(1), 40–48 (1995)

    Article  Google Scholar 

  4. Lin, C.-J., Lin, C.-R., Yu, S.-K., Chen, C.-T.: Hysteresis modeling and tracking control for a dual pneumatic artificial muscle system using Prandtl–Ishlinskii model. Mechatronics 2835–2845 (2015)

    Google Scholar 

  5. Minh, T.V., Tjahjowidodo, T., Ramon, H., Van Brussel, H.: Cascade position control of a single pneumatic artificial muscle–mass system with hysteresis compensation. Mechatronics 20(3), 402–414 (2010)

    Article  Google Scholar 

  6. Balasubramanian, K., Rattan, K.S.: Feedforward control of a non-linear pneumatic muscle system using fuzzy logic. In: The 12th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2003), St. Louis, Missouri, USA. IEEE (2003)

    Google Scholar 

  7. Thanh, T.D.C., Ahn, K.K.: Nonlinear PID control to improve the control performance of 2 axes pneumatic artificial muscle manipulator using neural network. Mechatronics 16(9), 577–587 (2006)

    Article  Google Scholar 

  8. Andrikopoulos, G., Nikolakopoulos, G., Manesis, S.: Pneumatic artificial muscles: a switching model predictive control approach. Control Eng. Pract. 21(12), 1653–1664 (2013)

    Article  Google Scholar 

  9. Andrikopoulos, G., Nikolakopoulos, G., Arvanitakis, I., Manesis, S.: Piecewise affine modeling and constrained optimal control for a pneumatic artificial muscle. IEEE Trans. Ind. Electron. 61(2), 904–916 (2014)

    Article  Google Scholar 

  10. Teramae, T., Noda, T., Morimoto, J.: Optimal control approach for pneumatic artificial muscle with using pressure-force conversion model. In: 2014 IEEE International Conference on Robotics and Automation (ICRA 2014), Hong Kong. IEEE (2014)

    Google Scholar 

  11. Osuka, K., Kimura, T., Ono, T.: H/sup infinity/control of a certain nonlinear actuator. In: 29th IEEE Conference on Decision and Control, Honolulu, Hawaii. IEEE (1990)

    Google Scholar 

  12. Tondu, B., Lopez, P.: Modeling and control of McKibben artificial muscle robot actuators. IEEE Control Syst. 20(2), 15–38 (2000)

    Article  Google Scholar 

  13. Hamerlain, M.: An anthropomorphic robot arm driven by artificial muscles using a variable structure control. In: 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems, Pittsburgh, Pennsylvania, USA. IEEE (1995)

    Google Scholar 

  14. Fan, J., Zhong, J., Zhao, J., Zhu, Y.: BP neural network tuned PID controller for position tracking of a pneumatic artificial muscle. Technol. Health Care 23(s2), S231–S238 (2015)

    Article  Google Scholar 

  15. Davis, S., Tsagarakis, N., Canderle, J., Caldwell, D.G.: Enhanced modelling and performance in braided pneumatic muscle actuators. Int. J. Rob. Res. 22(3–4), 213–227 (2003)

    Article  Google Scholar 

  16. Vo-Minh, T., Tjahjowidodo, T., Ramon, H., Van Brussel, H.: A new approach to modeling hysteresis in a pneumatic artificial muscle using the Maxwell-slip model. IEEE/ASME Trans. Mechatron. 16(1), 177–186 (2011)

    Article  Google Scholar 

  17. De Volder, M., Moers, A.J.M., Reynaerts, D.: Fabrication and control of miniature McKibben actuators. Sens. Actuators A: Phys. 166(1), 111–116 (2011)

    Article  Google Scholar 

  18. Chou, C.-P., Hannaford, B.: Static and dynamic characteristics of McKibben pneumatic artificial muscles. In: 1994 IEEE International Conference on Robotics and Automation, San Diego, California. IEEE (1994)

    Google Scholar 

  19. Chou, C.-P., Hannaford, B.: Measurement and modeling of McKibben pneumatic artificial muscles. IEEE Trans. Robot. Autom. 12(1), 90–102 (1996)

    Article  Google Scholar 

  20. Tondu, B.: Modelling of the McKibben artificial muscle: a review. J. Intell. Mater. Syst. Struct. 23(3), 225–253 (2012)

    Article  Google Scholar 

  21. Faudzi, A.A.M., Lazim, N.H.I.M., Suzumori, K.: Modeling and force control of thin soft McKibben actuator. IJAT 10(4), 487–493 (2016)

    Article  Google Scholar 

  22. Ahn, K.K., Huy Anh, H.P.: System modeling and identification the two-link pneumatic artificial muscle (PAM) manipulator optimized with genetic algorithms. In: 2006 SICE-ICASE International Joint Conference, Busan, Korea. IEEE (2006)

    Google Scholar 

  23. Kogiso, K., Naito, R., Sugimoto, K.: Application of game-theoretic learning to gray-box modeling of McKibben pneumatic artificial muscle systems. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan. IEEE (2013)

    Google Scholar 

  24. Kobayashi, W., Ito, K., Yamamoto, S.: Displacement control of water hydraulic McKibben muscles with load compensation. JFPS Int. J. Fluid Power Syst. 8(2), 107–112 (2014)

    Article  Google Scholar 

  25. Kurumaya, S., Nabae, H., Endo, G., Suzumori, K.: Design of thin McKibben muscle and multifilament structure. Sens. Actuators A: Phys. 26166–26174 (2017)

    Google Scholar 

  26. Trivedi, D., Rahn, C.D., Kier, W.M., Walker, I.D.: Soft robotics: biological inspiration, state of the art, and future research. Appl. Bionics Biomech. 5(3), 99–117 (2008)

    Article  Google Scholar 

  27. Yusoff, M.A.M., Faudzi, A.A.M., Sayahkarajy, M.: Experimental evaluation of a cylinder actuator control using McKibben muscle. Int. J. Integr. Eng. 11(4), 175–182 (2019)

    Google Scholar 

  28. Motor Control with Arduino: A Case Study in Data-Driven Modeling and Control Design. https://www.mathworks.com/company/newsletters/articles/motor-control-with-arduino-a-case-study-in-data-driven-modeling-and-control-design.html. Accessed 21 June 2020

  29. System Identification Toolbox. https://www.mathworks.com/products/sysid.html. Accessed 22 June 2020

  30. Slotine, J.-J.E., Li, W.: Applied Nonlinear Control. Prentice Hall, Englewood Cliffs (1991)

    Google Scholar 

  31. Gain Scheduling - MATLAB & Simulink. https://www.mathworks.com/help/control/gain-scheduled-controller-tuning.html. Accessed 23 June 2020

  32. Fixing PID, Part 2. https://www.controleng.com/articles/fixing-pid-part-2/. Accessed 23 June 2020

  33. Anti-Windup Control Using a PID Controller - MATLAB & Simulink. https://www.mathworks.com/help/simulink/slref/anti-windup-control-using-a-pid-controller.html. Accessed 23 June 2020

Download references

Acknowledgement

The authors would like to acknowledge the support provided by Ministry of Higher Education (MOHE) and Universiti Teknologi Malaysia (UTM) Collaborative Research Grant (CRG), Grant No. 08G30 and 08G31.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ahmad Athif Mohd Faudzi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mhd Yusoff, M.A., Mohd Faudzi, A.A., Hassan Basri, M.S. (2021). Feasibility of Pi Control for a Double-Acting Cylinder Actuated by Mckibben Muscles. In: Chew, E., et al. RiTA 2020. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-4803-8_33

Download citation

Publish with us

Policies and ethics