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<p>This research proposes an innovative framework integrating adaptive Digital Twin (DT) models with Multi-Level Inverter (MLI) control to improve energy efficiency in advanced rehabilitation systems. By utilizing real-time monitoring and adaptive adjustment of power parameters through DT technology, the method achieves precise and dynamic control of devices such as prosthetics and exoskeletons. The incorporation of MLI ensures smooth and efficient power delivery, reducing harmonic distortion and enhancing overall energy utilization. Key outcomes include a 14.05% increase in energy efficiency, an 8.12% decrease in power ripple, and a 24.03% improvement in system response accuracy, enabling real-time optimization tailored to patient-specific rehabilitation needs. Furthermore, the proposed approach lowers operational costs by 7.01% through optimized energy usage and extended system lifespan. These results highlight the potential of this innovative method to advance rehabilitation systems through the integration of adaptive control and real-time digital modeling.</p>

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Adaptive digital twin integration with multilevel inverter control for energy efficient smart rehabilitation systems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月12日

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  • Sara Mahmoudi Rashid,
  • Amir Rikhtehgar Ghiasi

摘要

This research proposes an innovative framework integrating adaptive Digital Twin (DT) models with Multi-Level Inverter (MLI) control to improve energy efficiency in advanced rehabilitation systems. By utilizing real-time monitoring and adaptive adjustment of power parameters through DT technology, the method achieves precise and dynamic control of devices such as prosthetics and exoskeletons. The incorporation of MLI ensures smooth and efficient power delivery, reducing harmonic distortion and enhancing overall energy utilization. Key outcomes include a 14.05% increase in energy efficiency, an 8.12% decrease in power ripple, and a 24.03% improvement in system response accuracy, enabling real-time optimization tailored to patient-specific rehabilitation needs. Furthermore, the proposed approach lowers operational costs by 7.01% through optimized energy usage and extended system lifespan. These results highlight the potential of this innovative method to advance rehabilitation systems through the integration of adaptive control and real-time digital modeling.