Stabilization Control of a Two-Wheeled Triple Link Inverted Pendulum System with Disturbance Rejection

  • M. F. MasromEmail author
  • N. M. Ghani
  • N. F. Jamin
  • N. A. A. Razali
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 538)


This paper focuses on the robust controller for triple Links inverted pendulum on two-wheeled system. The development of triple Link inverted pendulum on two-wheeled model using CAD based soft-ware, SimWise 4D is proposed. Interval Type-2 Fuzzy Logic Control (IT2FLC) is used as control algorithm for the system. This system is multi input and multi output system which means each motor in this system is controlled by one controller to achieve stability or upright position for these three links. The robustness of the controller is tested by applying disturbance to the model to observe the response from the model to handle the uncertainties. The performance of IT2FLC is compared with Type-1 Fuzzy Logic Control (T1FLC) to demonstrate best controller for the system. The experiment results concerning the angular position for each three Links and the maximum value of disturbance rejection for both controllers are obtained by using heuristic tuning for input and output gain control.


Triple links inverted pendulum on two-wheeled Type-1 fuzzy logic control Interval type-2 fuzzy logic control 



The work presented in the paper has been supported by Research Grant RDU170502 from the Research and Innovation Department, Universiti Malaysia Pahang.


  1. 1.
    Paliwal, S., Chopra, V., Singla, S.K.: Stabilization of mobile inverted pendulum using fuzzy PID controller (2016)Google Scholar
  2. 2.
    Ri, M., Huang, J., Ri, S., Yun, H., Kim, C.: Design of interval type-2 fuzzy logic controller for mobile wheeled inverted pendulum, pp. 535–540 (2016)Google Scholar
  3. 3.
    Yu, C., Wu, J.: Intelligent PID control for two-wheeled inverted pendulums, pp. 2–5 (2016)Google Scholar
  4. 4.
    Jaswal, A., Chand, S., Abdullah, A., Chakraborty, R.: Design and fabrication of self balancing two Wheeler. Int. J. Eng. Sci. 6(5), 5002–5005 (2016)Google Scholar
  5. 5.
    Ismail, H.A., Packianather, M.S., Grosvenor, R.I., Eldhukri, E.E.: The application of IWO in LQR controller design for the Robogymnast, vol. 2, pp. 274–279 (2015)Google Scholar
  6. 6.
    Tedeschi, F., Carbone, G.: Design of a novel leg-wheel hexapod walking robot (2017)CrossRefGoogle Scholar
  7. 7.
    Ahmad, S., Aminnuddin, M., Shukor, M.A.S.M.: Modular hybrid control for double-link two-wheeled mobile robot. In: International Conference on Computer and Communication Engineering, pp. 3–5 (2012)Google Scholar
  8. 8.
    Goher, K.M., Tokhi, M.O.: A new configuration of two-wheeled inverted pendulum: a lagrangian based mathematical approach, pp. 1–5 (2010)Google Scholar
  9. 9.
    Urakubo, T., Tsuchiya, K., Tsujita, K.: Motion control of a two-wheeled mobile robot. Adv. Robot. 1864, 2012 (2001)Google Scholar
  10. 10.
    Naik, K.A., Gupta, C.P.: Performance comparison of type-1 and type-2 fuzzy logic systems. In: 4th IEEE International Conference on Signal Processing, Computing and Control, pp. 72–76 (2017)Google Scholar
  11. 11.
    Jamin, N.F., Ghani, N.M.: Two-wheeled wheelchair stabilization control using fuzzy logic controller based particle swarm optimization, pp. 78–83 (2016)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • M. F. Masrom
    • 1
    Email author
  • N. M. Ghani
    • 1
  • N. F. Jamin
    • 1
  • N. A. A. Razali
    • 1
  1. 1.Department of Electrical and Electronics EngineeringUniversiti Malaysia PahangPekanMalaysia

Personalised recommendations