Balancing control of inverted wedge system using neuro Fuzzy method

Authors

  • Thanh Tan Nguyen Tra Vinh University, Vietnam
  • Minh Tam Nguyen Ho Chi Minh City University of Technology and Education, Vietnam
  • Thi Thanh Hoang Le Ho Chi Minh City University of Technology and Education, Vietnam
  • Van Dong Hai Nguyen Ho Chi Minh City University of Technology and Education, Vietnam

Corressponding author's email:

thanhtantvu@gmail.com

Keywords:

balance, inverted wedge, fuzzy control, neuro fuzzy, LQR

Abstract

In this article, the authors use three control algorithms on the inverted wedge, including of LQR, Fuzzy Control and neuro-fuzzy. Simulation results show that all methods can balance the inverted wedge. Besides, the authors build successfully the experimental inverted wedge model which is based on computer communication between Matlab software and DSP TMS320F28335 card. Experimental results show that neuro-fuzzy control method can stabilize inverted wedge in vertical position. The values of angle and position of load vibrate around the expected equilibrium position.

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References

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Chun-Hsien Tsai, Hung-Yuan Chung, Fang-Ming Yu, Neuro-Sliding Mode Control With Its Applications to Seesaw Systems, IEEE Transactions on, pp. 124 – 134, 2004.

Jeng-Hann Li, Tzuu-Hseng S. Li, Ting-Han Ou, Design and Implementation of Fuzzy Sliding-Mode Controller for a Wedge Balancing System, Journal of Intelligent and Robotic Systems, Volume 37 Issue 3, pp. 285-306, 2003.

Shinq-Jen Wu, Cheng-Tao Wu, Yung-Yi chiou, Chin-Teng Lin, Yi-Nung Chung, Balancing Control of Sliding Inverted-Wedge System: classical- method- based compensation, IEEE International Conference on SMC '06, pp. 1349 – 1354, 2006.

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Published

28-09-2018

How to Cite

[1]
T. T. Nguyen, M. T. Nguyen, T. T. H. Le, and V. D. H. Nguyen, “Balancing control of inverted wedge system using neuro Fuzzy method”, JTE, vol. 13, no. 5, pp. 88–95, Sep. 2018.

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Section

Research Article

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