IJRME – Volume 1 Issue 2 Paper 6


Author’s Name :  P Vivekanandan | R Sambasivam | P Devendran

Volume 01 Issue 02  Year 2014  ISSN No:  2349-3860  Page no: 24-27



The main objective of this paper is to investigate the performance of inverted pendulum using pole on cart system. Inverted pendulum system is unstable without control, that is, the pendulum wills simply fall over if the cart isn’t moved to balance it and naturally falls downward because of gravity. Thus, the inverted pendulum system is inherently unstable. In order to keep it upright, or stabilize this system, one needs to manipulate it, either vertically or horizontally and it requires a continuous correction mechanism to stay upright since the system is unstable, non-linear and non-minimum phase behavior. To overcome this problem, the fuzzy logic controller will be designed. The Fuzzy Logic Controller has been chosen to stabilize the pendulum rod and keeping the cart in a desired position. Fuzzy logic has provided a simple way without going through the mathematical approach as conventional controller in order to arrive at a definite conclusion based upon nonlinear and an unstable of inverted pendulum system. Besides that, Fuzzy logic control system (FLC) was chosen as the control technique because of its ability to deal with nonlinear systems, as well as its intuitive nature. One special feature of fuzzy logic control is that it utilizes the expertise of humans to control the physical system, so that complex system can be controlled without extensive modeling of the relationship between the input and output of the system.


  1. L. A. Zadeh, “Fuzzy sets,” Information and Computation, vol. 8,pp. 338–353, 1965.
  2. B. Xiao, Q. Hu, and Y. Zhang, “Adaptive sliding mode fault tolerant attitude tracking control for flexible spacecraft under actuator saturation,” IEEE Transactions on Control Systems Technology, vol. 20, no. 6, pp. 1605–1612, 2012.
  3. B. Xiao, Q. Hu, and Y. Zhang, “Fault-tolerant attitude control for flexible spacecraft without angular velocity magnitude measurement,” Journal of Guidance,Control, and Dynamics, vol.34, no. 5, pp. 1556–1561, 2011.
  4. Y. Zhao,W. Sun, and H. Gao, “Robust control synthesis for seat suspension systems with actuator saturation and time-varying input delay,” Journal of Sound and Vibration, vol. 329, no. 21, pp.4335–4353, 2010.
  5. L. Wu, X. Su, and P. Shi, “Sliding mode control with bounded??2 gain performance of Markovian jump singular time-delay systems,” Automatica, vol. 48, no. 8, pp. 1929–1933, 2012.
  6. Q. Hu, “Sliding mode maneuvering control and active vibration damping of three-axis stabilized flexible spacecraft with actuator dynamics,” Nonlinear Dynamics, vol. 52, no. 3, pp. 227–248,2008
  7. G. Pujol, “Reliable ??8 control of a class of uncertain inter connected systems: an LMI approach,”International Journal of Systems Science, vol. 40, no.6, pp. 649–657, 2009.
  8. Q. Zheng and F. Wu, “Nonlinear ??8 control designs with axisymmetric spacecraft control,” Journal of Guidance, Control,and Dynamics, vol. 32, no. 3, pp. 850–859, 2009.
  9. W. Sun, H. Gao Sr., and O. Kaynak, “Finite frequency ??8 control for vehicle active suspension systems,” IEEE Transactions on Control Systems Technology, vol. 19, no. 2, pp. 416–422, 2011.
  10. S. Yin, H. Luo, and S.Ding, “Real-time implementation of fault tolerant control systems with performance optimization,” IEEE Transactions on Industrial Electronics, vol. 61, no. 5, pp. 2402–2411, 2013.
  11. M. V. Levskii, “Optimal control of reorientation of a spacecraft using free trajectory method,” Cosmic Research, vol. 49, no. 2,pp. 131–149, 2011.
  12. E. M. Queen and L. Silver berg, “Optimal control of a rigid bodywith dissimilar actuators,” Journal of Guidance, Control, and Dynamics, vol. 19, no. 3, pp. 738–740, 1996.
  13. S. Yin, S. X. Ding, A. H. A. Sari, and H. Hao, “Data-driven monitoring for stochastic systems and its application on batch process,” International Journal of Systems Science, vol. 44, no. 7,pp. 1366–1376, 2013.
  14. S. Yin, S. X. Ding, A. Haghani, H. Hao, and P. Zhang, “A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process,” Journal of Process Control, vol. 22, no. 9, pp.1567–1581, 2012.
  15. S. Yin, X. Yang, and H. R. Karimi, “Data-driven adaptive observer for fault diagnosis,” Mathematical Problems in Engineering,vol. 2012, Article ID 832836, 21 pages, 2012.
  16. S.-J. Dong, Y.-Z. Li, J. Wang, and J. Wang, “Fuzzy incremental control algorithm of loop heat pipe cooling system for spacecraft applications,” Computers&Mathematics with Applications,vol. 64, no. 5, pp. 877–886, 2012.
  17. Z. Gao, X. Shi, and S.X.Ding, “Fuzzy state/disturbance observer design for T-S fuzzy systems with application to sensor fault estimation,” IEEE Transactions on Systems, Man, and Cybernetics B, vol. 38, no. 3, pp. 875–880, 2008.
  18. S. Udomsin, “Inverted pendulum control,” KKU Engineering Journal, vol. 25, pp. 41–65, 2013