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<p>Lower-limb exoskeleton (LLEX) robots are becoming increasingly popular for aiding individuals with disabilities. However, the tracking performance of LLEX robots is significantly affected by system uncertainties and disturbances. This study introduces robust, optimal integral sliding mode control (SMC) in combination with model-free technique-based time delay estimation (TDE) to improve the trajectory tracking accuracy of LLEX robot with uncertainties. Moreover, an optimization algorithm known as particle swarm optimization algorithm (PSO) is applied to obtain an optimal sliding surface parameter. The stability of the proposed method (PSOSMC-TDE) is theoretically approved using the Lyapunov function. To further validate its effectiveness, both simulations with a 3D LLEX model and experiments on a physical LLEX platform were conducted, considering uncertainties such as noise, friction, and external disturbances. The results demonstrate that PSOSMC-TDE achieves precise trajectory tracking while maintaining robust and stable control signals, outperforming conventional SMC-TDE and nonsingular fast terminal SMC-TDE methods.</p>

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An Optimal Integral Sliding Mode Control Based Time Delay Estimation for Nonlinear Lower Limb Exoskeleton Robot

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月26日

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  • Alrawda Alsaied,
  • Ke Li,
  • Jiashuai Wang,
  • Ghazally I. Y. Mustafa

摘要

Lower-limb exoskeleton (LLEX) robots are becoming increasingly popular for aiding individuals with disabilities. However, the tracking performance of LLEX robots is significantly affected by system uncertainties and disturbances. This study introduces robust, optimal integral sliding mode control (SMC) in combination with model-free technique-based time delay estimation (TDE) to improve the trajectory tracking accuracy of LLEX robot with uncertainties. Moreover, an optimization algorithm known as particle swarm optimization algorithm (PSO) is applied to obtain an optimal sliding surface parameter. The stability of the proposed method (PSOSMC-TDE) is theoretically approved using the Lyapunov function. To further validate its effectiveness, both simulations with a 3D LLEX model and experiments on a physical LLEX platform were conducted, considering uncertainties such as noise, friction, and external disturbances. The results demonstrate that PSOSMC-TDE achieves precise trajectory tracking while maintaining robust and stable control signals, outperforming conventional SMC-TDE and nonsingular fast terminal SMC-TDE methods.