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Control System of Two-Wheel Self-Balancing Vehicle

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Abstract

This study mainly concerns a motion model and the main control algorithm of two-wheel self-balancing vehicle models. Details of the critical parameters fetching and output value of two-wheel self-balancing vehicle models are introduced, including those concerning balance control, speed control and direction control. An improved cascade coupling control scheme is proposed for two-wheel vehicles, based on a proportional-integral-derivative (PID) control algorithm. Moreover, a thorough comparison between a classic control system and the improved system is provided, and all aspects thereof are analyzed. It is determined that the control performance of the two-wheel self-balancing vehicle system based on the PID control algorithm is reliable, enabling the vehicle body to maintain balance while moving smoothly along a road at a fast average speed with better practical performance.

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References

  1. YANG Z C, LV K. Study on two-wheeled self-balancing electric vehicle based on fuzzy PD control method [J]. Control Engineering of China, 2016, 23(3): 366–370 (in Chinese).

    Google Scholar 

  2. WANG Y, YANG W C, CHEN X Q, et al. Study of two-wheeled car system based on freescale microcontroller [J]. Electronics World, 2013(13): 10–11 (in Chinese).

  3. LU X, XIAO Z J, NAN L L, et al. Design based on KEA128 electromagnetic navigation two-wheel self-balancing balanced vehicle [J]. Mechanical and Electrical Technology, 2019(1): 4–6 (in Chinese).

  4. QIAO W G. Developing of a dual-wheel self-balancing vehicle using double PID cascade control [D]. Changchun, China: Jilin University, 2017 (in Chinese).

    Google Scholar 

  5. QIAN Q W. Research on modeling and control method of two-wheeled self-balancing vehicle pendulum robot [D]. Harbin: Harbin University of Science and Technology, 2019 (in Chinese).

    Google Scholar 

  6. LI S S. Research on intelligent vehicle design with MCU [D]. Nanjing, China: Nanjing University of Science and Technology, 2013 (in Chinese).

    Google Scholar 

  7. LIN S C, TSAI C C. Development of a self-balancing human transportation vehicle for the teaching of feedback control [J]. IEEE Transactions on Education, 2009, 52(1): 157–168.

    Article  Google Scholar 

  8. ZHOU M D, KANG K, CAI P R, et al. Design and implementation of two-wheeled self-balancing vehicle control system [J]. Techniques of Automation Applications, 2014, 33(10): 4–8 (in Chinese).

    Google Scholar 

  9. FENG Z Y, ZENG H, ZHANG L, et al. Angle measurement based on gyroscope and accelerometer signal fusion [J]. Journal of Southwest China Normal University (Natural Science Edition), 2011, 36(4): 137–141 (in Chinese).

    Google Scholar 

  10. WANG W, DENG S P, ZHANG X L, et al. Research on control method of two-wheeled self-balancing vehicle based on attitude detection [J]. Equipment Manufacturing Technology, 2019(10): 18–22 (in Chinese).

  11. TAI Y M, GENG Y F, ZHANG P J, et al. Design of upright self-balancing smart car based on camera sensor [J]. Computer Measurement and Control, 2016, 24(1): 99–101 (in Chinese).

    Google Scholar 

  12. PASAYE J J R, VALENCIA J A B, PÉREZ F J. Tilt measurement based on an Accelerometer, a Gyro and a Kalman Filter to control a self-balancing vehicle [C]//2013 IEEE International Autumn Meeting on Power Electronics and Computing (ROPEC). Morelia, Mexico: IEEE, 2013: 1–5.

    Google Scholar 

  13. ZHANG Y H. Application of complementary filter in attitude solution of quaternion method [J]. Telecom World, 2015(13): 27–28 (in Chinese).

  14. LIN W J, HUANG W J, CAI J Q. System design of two-wheel self-balancing vehicle based on quaternion complementary filtering and pid control algorithm [J]. Software Guide, 2016, 15(6): 80–82 (in Chinese).

    Google Scholar 

  15. CHEN L, WANG H, HUANG Y Z, et al. Robust hierarchical sliding mode control of a two-wheeled self-balancing vehicle using perturbation estimation [J]. Mechanical Systems and Signal Processing, 2020, 139: 106584.

    Article  Google Scholar 

  16. Freescale Intelligent Vehicle Competition Office. The electromagnetic Group Self-balancing Driving Reference Design Scheme (version 2. 0) for the 7th National College Students “Freescale” Cup Intelligent Vehicle Competition [EB/OL]. (2012-03-01) [2021-03-20]. https://smartcar.cdstm.cn/ (in Chinese).

  17. WANG Y J, MENG W, LI L E, et al. Improved multiloop control of two-wheel upright vehicle [J]. Automation and Instrumentation, 2019, 34(12): 39–44 (in Chinese).

    Google Scholar 

  18. VELAZQUEZ M, CRUZ D, GARCIA S, et al. Velocity and motion control of a self-balancing vehicle based on a cascade control strategy [J]. International Journal of Advanced Robotic Systems, 2016, 13(3): 106.

    Article  Google Scholar 

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Authors and Affiliations

  1. College of Automation and Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China

    Hao Ren  (任淏)

  2. School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China

    Cong Zhou  (周聪)

Authors
  1. Hao Ren  (任淏)
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  2. Cong Zhou  (周聪)
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Correspondence to Hao Ren  (任淏).

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Ren, H., Zhou, C. Control System of Two-Wheel Self-Balancing Vehicle. J. Shanghai Jiaotong Univ. (Sci.) 26, 713–721 (2021). https://doi.org/10.1007/s12204-021-2361-x

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  • DOI: https://doi.org/10.1007/s12204-021-2361-x

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