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Adaptive Fuzzy Backstepping Sliding Mode Control for Omni Mobile Robot Over Network Control System

  • Minh Ngoc PhamEmail author
  • Vinh Quang Thai
  • Duyen Kim Thi Ha
  • Tien Manh Ngo
  • Cuong Manh Nguyen
  • Manh Van Tran
  • Hiep Quang Do
Chapter
  • 4 Downloads
Part of the Studies in Computational Intelligence book series (SCI, volume 899)

Abstract

The performance characteristic of the control system over a network can be significantly affected by network delay effects. These effects can be more exacerbated when data loss occurs during network communication. Thus, in this paper network effects could be resolved by utilizing a structure of gain scheduler middleware (GSM) in setting robot path-tracking. Simultaneously, this teleoperation control approach combines with the Adaptive Backstepping Sliding Mode controller based on self—tuning Fuzzy adapting control parameters to stabilize the control system. The simulation result of the proposed controller operating over data network depicts that the control quality would be improved than normal Backstepping Sliding Mode Control without GSM methodology even in disturbance environment.

References

  1. 1.
    Thi, K.D.H., Nguyen, M.C., Vo, H.T., Tran, V.M., Nguyen, D.D., Bui, A.D.: Trajectory tracking control for four-wheeled omnidirectional mobile robot using Backstepping technique aggregated with sliding mode control. In: 2019 First International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP), pp. 131–134 (2019)Google Scholar
  2. 2.
    Gao, Z., Yang, Y., Du, Y., Zhang, Y., Wang, Z.: Kinematic modeling and trajectory tracking control of a wheeled omni-directional mobile logistics platform. DEStech Trans. Eng. Technol. Res., no. apetc (2017)Google Scholar
  3. 3.
    Li, W., Yang, C., Jiang, Y., Liu, X., Su, C.-Y.: Motion planning for omnidirectional wheeled mobile robot by potential field method. J. Adv. Transp. 2017, 11 (2017)Google Scholar
  4. 4.
    Abiyev, R.H., Günsel, I.S., Akkaya, N., Aytac, E., Çağman, A., Abizada, S.: Fuzzy control of omnidirectional robot. Procedia Comput. Sci. 120, 608–616 (2017)CrossRefGoogle Scholar
  5. 5.
    Wang, C., Liu, X., Yang, X., Hu, F., Jiang, A., Yang, C.: Trajectory tracking of an omni-directional wheeled mobile robot using a model predictive control strategy. Appl. Sci. 8(2), 231 (2018)CrossRefGoogle Scholar
  6. 6.
    Santos, J., Conceiçao, A.G.S., Santos, T.L.M.: Trajectory tracking of omni-directional mobile robots via predictive control plus a filtered smith predictor. IFAC-PapersOnLine 50(1), 10250–10255 (2017)CrossRefGoogle Scholar
  7. 7.
    Ovalle, L., Ríos, H., Llama, M., Santibáñez, V., Dzul, A.: Omnidirectional mobile robot robust tracking: sliding-mode output-based control approaches. Control Eng. Pract. 85, 50–58 (2019)CrossRefGoogle Scholar
  8. 8.
    Vieira, H.S., de Paiva, E.C., Moriguchi, S.K., Carvalho, J.R.H.: Unified Backstepping Sliding Mode Framework for Airship Control Design. arXiv Prepr. arXiv:1909.03143 (2019)
  9. 9.
    Truong, H.V.A., Tran, D.T., To, X.D., Ahn, K.K., Jin, M.: Adaptive fuzzy backstepping sliding mode control for a 3-DOF hydraulic manipulator with nonlinear disturbance observer for large payload variation. Appl. Sci. 9(16), 3290 (2019)CrossRefGoogle Scholar
  10. 10.
    Jia, Z., Yu, J., Mei, Y., Chen, Y., Shen, Y., Ai, X.: Integral backstepping sliding mode control for quadrotor helicopter under external uncertain disturbances. Aerosp. Sci. Technol. 68, 299–307 (2017)CrossRefGoogle Scholar
  11. 11.
    Liang, X., Wan, L., Blake, J.I.R., Shenoi, R.A., Townsend, N.: Path following of an underactuated AUV based on fuzzy backstepping sliding mode control. Int. J. Adv. Robot. Syst. 13(3), 122 (2016)CrossRefGoogle Scholar
  12. 12.
    Mendez-Monroy, P.E., Dominguez, I.S., Bassam, A., Tzuc, O.M.: Control-scheduling codesign for ncs based fuzzy systems. Int. J. Comput. Commun. Control 13(2), 251–267 (2018)CrossRefGoogle Scholar
  13. 13.
    Lin, Y., Wang, J., Han, Q.-L., Jarvis, D.: Distributed control of networked large-scale systems based on a scheduling middleware. In: IECON 2017-43rd Annual Conference of the IEEE Industrial Electronics Society, pp. 5523–5528 (2017)Google Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Minh Ngoc Pham
    • 1
    Email author
  • Vinh Quang Thai
    • 1
  • Duyen Kim Thi Ha
    • 2
  • Tien Manh Ngo
    • 3
  • Cuong Manh Nguyen
    • 3
  • Manh Van Tran
    • 3
  • Hiep Quang Do
    • 4
  1. 1.Institute of Information TechnologyVietnam Academy of Science and TechnologyHanoiVietnam
  2. 2.Hanoi University of IndustryHanoiVietnam
  3. 3.Institute of PhysicsVietnam Academy of Science and TechnologyHanoiVietnam
  4. 4.University of Economics-Technology for IndustriesHanoiVietnam

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