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Adaptive Sliding Mode Trajectory Tracking Control for WMR Considering Skidding and Slipping via Extended State Observer

Author

Listed:
  • Gang Wang

    (School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Chenghui Zhou

    (School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Yu Yu

    (School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Xiaoping Liu

    (School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Abstract

When the wheeled mobile robot (WMR) is required to perform specific tasks in complex environment, i.e., on the forestry, wet, icy ground or on the sharp corner, wheel skidding and slipping inevitably occur during trajectory tracking. To improve the trajectory tracking performance of WMR under unknown skidding and slipping condition, an adaptive sliding mode controller (ASMC) design approach based on the extended state observer (ESO) is presented. The skidding and slipping is regarded as external disturbance. In this paper, the ESO is introduced to estimate the lumped disturbance containing the unknown skidding and slipping, parameter variation, parameter uncertainties, etc. By designing a sliding surface based on the disturbance estimation, an adaptive sliding mode tracking control strategy is developed to attenuate the lumped disturbance. Simulation results show that higher precision tracking and better disturbance rejection of ESO-ASMC is realized for linear and circular trajectory than the ASMC scheme. Besides, experimental results indicate the ESO-ASMC scheme is feasible and effective. Therefore, ESO-ASMC scheme can enhance the energy efficiency for the differentially driven WMR under unknown skidding and slipping condition.

Suggested Citation

  • Gang Wang & Chenghui Zhou & Yu Yu & Xiaoping Liu, 2019. "Adaptive Sliding Mode Trajectory Tracking Control for WMR Considering Skidding and Slipping via Extended State Observer," Energies, MDPI, vol. 12(17), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:17:p:3305-:d:261443
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    Citations

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    Cited by:

    1. Yung-Hsiang Chen & Yung-Yue Chen, 2022. "Trajectory Tracking Design for a Swarm of Autonomous Mobile Robots: A Nonlinear Adaptive Optimal Approach," Mathematics, MDPI, vol. 10(20), pages 1-21, October.
    2. Yubo Liu & Junlong Fang & Kezhu Tan & Boyan Huang & Wenshuai He, 2020. "Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM," Energies, MDPI, vol. 13(22), pages 1-18, November.

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