Electrical and Computer Engineering

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    Fuzzy Sliding Mode Control for Dynamic Walking Assistance in Lower Limb Exoskeletons
    (Mekelle University, 2025-04-23) Tsega Hailemariam Gebrecherkos
    In recent years, the development of wearable exoskeleton robots has gained significant attention due to their potential to assist individuals with mobility impairments. These robotic systems are designed to enhance, assist, or restore motor functions, particularly for those with disabilities or injuries affecting the lower limbs. However, controlling lower limb exoskeletons presents substantial challenges due to the nonlinear dynamics of human gait and the need for adaptation to varying user requirements and environmental conditions. This thesis proposes a Fuzzy Sliding Mode Control (FSMC) strategy as an advanced hybrid control solution for a 2-DOF lower limb exoskeleton robot designed to assist dynamic walking. The key novelty of the proposed method lies in the integration of fuzzy logic into the sliding mode control framework, where the fuzzy inference system dynamically adjusts the control gains based on real-time tracking errors and their rates of change. This adaptive mechanism enables FSMC to strike a balance between the high robustness of sliding mode control and the smooth response characteristics of fuzzy logic systems.The proposed FSMC was benchmarked against classical Sliding Mode Control (SMC) and Quasi-SMC across multiple walking scenarios, including variations in walking speed and random stop-start motions. Unlike conventional SMC methods—which often struggle with nonlinearities, parameter uncertainties, and gait variability—the FSMC approach offers superior adaptability. Simulation results demonstrate that FSMC outperforms classical SMC and Quasi-SMC in both tracking accuracy and robustness. Under increased walking speeds, FSMC exhibited the lowest increase in error (5.57% in Case 1, 9.68% in Case 2) compared to 186.16% and 116% for SMC, and 169% and 162% for Quasi-SMC, respectively. In random motion scenarios, FSMC achieved the lowest sum of squared tracking errors, confirming its effectiveness under dynamic conditions. Furthermore, FSMC significantly reduced control signal chattering, which not only improves tracking but also reduces mechanical wear, enhancing the exoskeleton’s longevity. In conclusion, this study demonstrates that FSMC is a superior control strategy for lower limb exoskeletons operating under uncertain and dynamic walking conditions. Its ability to combine adaptability, robustness, and smoothness makes it a strong candidate for future real-time implementations and clinical applications in mobility assistance and gait rehabilitation