Skip to main content
Log in

Double-loop fuzzy motion control with CoG supervisor for two-wheeled self-balancing assistant robots

  • Published:
International Journal of Dynamics and Control Aims and scope Submit manuscript

Abstract

Though adding manipulator arms gives a two-wheeled self-balancing assistant robot (TSAR) the ability of fetching object, the degenerated balancing performance would occur without considering the effect of robot center-of-gravity (CoG) position when the manipulator arms operate. To tackle this problem, a double-loop fuzzy motion control (DFMC) system is proposed to control the TSAR moving, turning, and reaching a desired position while keeping TSAR balanced. A CoG supervising controller is proposed to control the body pitch angle of TSAR with respect to manipulator arms operate. To show the effectiveness of the CoG supervising controller, three engagement scenarios are applied in the presence of external disturbances and system uncertainties. The experimental results show that the proposed DFMC system with considering CoG supervising controller can achieve better motion performance than without considering that. Further, a visual serving technique is used for doing object recognition and a fuzzy guidance control (FGC) is proposed to let the TSAR can implement the object tracking mission. The experimental results show that not only the DFMC system can maintain TSAR balance but also the FGC system can lead TSAR to fetch target object successfully.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Huang J, Guan ZH, Matsuno T, Fukuda T, Sekiyama K (2010) Sliding-mode velocity control of mobile-wheeled inverted-pendulum systems. IEEE Trans Robot 26(4):750–758

    Article  Google Scholar 

  2. Key MS, Jeon CG, Yoo DS (2012) Sliding mode control for a two-wheeled inverted pendulum mobile robot driving on uniform slopes. In: International conference on control, automation and systems, pp 2159–2162

  3. Hirata K, Kamatani M, Murakami T (2013) Advanced motion control of two-wheel wheelchair for slope environment. In: 39th annual conference of the IEEE Industrial Electronics Society, pp 6436–6441

  4. Zheng N, Zhang Y, Guo Y, Zhang X (2017) Hierarchical fast terminal sliding mode control for a self-balancing two-wheeled robot on uneven terrains. In: Proceedings of the 36th Chinese control conference, pp 4762–4767

  5. Lee H, Jung S (2012) Balancing and navigation control of a mobile inverted pendulum robot using sensor fusion of low cost sensors. Mechatronics 22(1):95–105

    Article  Google Scholar 

  6. Pratama D, Binugroho EH, Ardilla F (2015) Movement control of two wheels balancing robot using cascaded PID controller. In: 2015 international electronics symposium, pp 94–99

  7. Mahmoud MS, Nasir MT (2017) Robust control design of wheeled inverted pendulum assistant robot. IEEE/CAA J Autom Sin 4(4):628–638

    Article  MathSciNet  Google Scholar 

  8. Uddin N, Nugroho TA, Pramudito WA (2017) Stabilizing two-wheeled robot using linear quadratic regulator and states estimation. In: 2017 2nd international conferences on information technology, information systems and electrical engineering, pp 229–234

  9. Xu JX, Guo ZQ, Lee TH (2014) Design and implementation of integral sliding-mode control on an under actuated two-wheeled mobile robot. IEEE Trans Ind Electron 61(7):3671–3681

    Article  Google Scholar 

  10. Fukushima H, Muro K, Matsuno F (2015) Sliding-mode control for transformation to an inverted pendulum mode of a mobile robot with wheel-arms. IEEE Trans Ind Electron 62(7):4257–4266

    Article  Google Scholar 

  11. Kim S, Kwon S (2017) Nonlinear optimal control design for underactuated two-wheeled inverted pendulum mobile platform. IEEE/ASME Trans Mechatron 22(6):2803–2808

    Article  Google Scholar 

  12. Esmaeili N, Alfi A, Khosravi H (2017) Balancing and trajectory tracking of two-wheeled mobile robot using backstepping sliding mode control: design and experiments. J Intell Robot Syst 87(3–4):601–613

    Article  Google Scholar 

  13. Hsu CF, Su CT, Kao WF, Lee BK (2018) Vision-based line-following control of a two-wheel self-balancing robot. In: 2018 international conference of machine learning and cybernetics, pp 319–324

  14. Huang J, Ri M, Wu D, Ri S (2018) Interval type-2 fuzzy logic modeling and control of a mobile two-wheeled inverted pendulum. IEEE Trans Fuzzy Syst 26(4):2030–2038

    Article  Google Scholar 

  15. Yang C, Li Z, Li J (2013) Trajectory planning and optimized adaptive control for a class of wheeled inverted pendulum vehicle models. IEEE Trans Cybern 43(1):24–36

    Article  Google Scholar 

  16. Cui R, Guo J, Mao Z (2015) Adaptive backstepping control of wheeled inverted pendulums models. Nonlinear Dyn 79(1):501–511

    Article  MathSciNet  Google Scholar 

  17. Jiang L, Qiu H, Wu Z, He J (2016) Active disturbance rejection control based on adaptive differential evolution for two-wheeled self-balancing robot. In: 2016 Chinese control and decision conference, pp 6761–6766

  18. Chiu CH, Peng YF, Lin YW (2011) Robust intelligent backstepping tracking control for wheeled inverted pendulum. Soft Comput 15(10):2029–2040

    Article  Google Scholar 

  19. Yang C, Li Z, Cui R, Xu B (2014) Neural network-based motion control of underactuated wheeled inverted pendulum models. IEEE Trans Neural Netw Learn Syst 25(11):2004–2016

    Article  Google Scholar 

  20. Unluturk A, Aydogdu O (2017) Adaptive control of two-wheeled mobile balance robot capable to adapt different surfaces using a novel artificial neural network-based realtime switching dynamic controller. Int J Adv Robot Syst 14(2):1–9

    Article  Google Scholar 

  21. Yan J, Yang H (2016) Hierarchical reinforcement learning based self-balancing algorithm for two-wheeled robots. Open Electr Electron Eng J 10:69–79

    Article  Google Scholar 

  22. Iwendi C, Alqarni MA, Anajemba JH, Alfakeeh AS, Zhang Z, Bashir AK (2019) Robust navigational control of a two-wheeled self-balancing robot in a sensed enviroment. IEEE Access 7:82337–82348

    Article  Google Scholar 

  23. Wu TF (2018) Tracking control of wheeled mobile robots using fuzzy CMAC neural networks. J Internet Technol 19(6):1853–1869

    Google Scholar 

  24. Máthé K, Buşoniu L, Barabás L, Iuga C, Miclea L, Braband J (2016) Vision-based control of a quadrotor for an object inspection scenario. In: 2016 international conference on unmanned aircraft systems, pp 849–857

  25. Wang H, Guo D, Liang X, Chen W, Hu G, Leang KK (2017) Adaptive vision-based leader-follower formation control of mobile robots. IEEE Trans Ind Electron 64(4):2893–2902

    Article  Google Scholar 

  26. Gupta M, Kumar S, Behera L, Subramanian VK (2017) A novel vision-based tracking algorithm for a human-following mobile robot. IEEE Trans Syst Man Cybern Syst 47(7):1415–1427

    Article  Google Scholar 

  27. Wang M, Liu Y, Su D, Liao Y, Shi L, Xu J, Miro JV (2018) Accurate and real-time 3-D tracking for the following robots by fusing vision and ultrasonar information. IEEE/ASME Trans Mechatron 23(3):997–1006

    Article  Google Scholar 

  28. Lee GH, Jung S (2013) Line tracking control of a two-wheeled mobile robot using visual feedback. Int J Adv Robot Syst 10(177):1–8

    Google Scholar 

  29. Ye W, Li Z, Yang C, Sun J, Su CY, Lu R (2016) Vision-based human tracking control of a wheeled inverted pendulum robot. IEEE Trans Cybern 46(11):2423–2434

    Article  Google Scholar 

  30. Kung F (2017) Design of agile two-wheeled robot with machine vision. In: 2017 international conference on robotics, automation and sciences, pp 1–5

  31. Hsu CF, Wong KY (2016) On-line constructive fuzzy sliding-mode control for voice coil motors. Appl Soft Comput 47(10):415–423

    Article  Google Scholar 

  32. Hsu CF, Lee TT (2017) Emotional fuzzy sliding-mode control for unknown nonlinear systems. Int J Fuzzy Syst 19(3):942–953

    Article  MathSciNet  Google Scholar 

  33. Khooban MH, Alfi A, Abadi DNM (2013) Teaching–learning-based optimal interval type-2 fuzzy PID controller design: a nonholonomic wheeled mobile robots. Robotica 31(7):1059–1071

    Article  Google Scholar 

  34. Huang D, Zhai J, Ai W, Fei S (2016) Disturbance observer-based robust control for trajectory tracking of wheeled mobile robots. Neurocomputing 198(1):74–79

    Article  Google Scholar 

  35. Zhai JY, Song ZB (2019) Adaptive sliding mode trajectory tracking control for wheeled mobile robots. Int J Control 92(10):2255–2262

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the associate editor and the reviewers for their valuable comments. The authors appreciate the partial financial support from the Ministry of Science and Technology, Taiwan, under Grants MOST 105-2628-E-032-001-MY3.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chun-Fei Hsu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hsu, CF., Kao, WF. Double-loop fuzzy motion control with CoG supervisor for two-wheeled self-balancing assistant robots. Int. J. Dynam. Control 8, 851–866 (2020). https://doi.org/10.1007/s40435-020-00617-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40435-020-00617-y

Keywords

Navigation