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A wearable rehabilitation robot functions to fulfill recovery process of limb functionality and assist physiotherapists. This paper presents a gain optimized adaptive control system for a wearable rehabilitation robot. The controller's gains defined as optimization problem for control system of wearable rehabilitation robot determined by Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). We also introduced Initialized Model Reference Adaptive Controller (IMRAC) for real-time joint trajectory tracking. The controller's gains are adjusted by the gradient-based method and initialized by GA and PSO. A prototype model of 4 DoF lower limb rehabilitation robot has been developed to observe the closed-loop performance of IMRAC for bipedal with human walking. Statistical analysis shows the robustness of proposed gain optimized adaptive controller ascertained its efficient performance of joint trajectory tracking in real-time.

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Swarm Based Adaptive Control of Wearable Rehabilitation Robot

  • 会议论文

  • 发表日期：

    2025年

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  • Mohammad Soleimani Amiri,
  • Rizauddin Ramli

摘要

A wearable rehabilitation robot functions to fulfill recovery process of limb functionality and assist physiotherapists. This paper presents a gain optimized adaptive control system for a wearable rehabilitation robot. The controller's gains defined as optimization problem for control system of wearable rehabilitation robot determined by Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). We also introduced Initialized Model Reference Adaptive Controller (IMRAC) for real-time joint trajectory tracking. The controller's gains are adjusted by the gradient-based method and initialized by GA and PSO. A prototype model of 4 DoF lower limb rehabilitation robot has been developed to observe the closed-loop performance of IMRAC for bipedal with human walking. Statistical analysis shows the robustness of proposed gain optimized adaptive controller ascertained its efficient performance of joint trajectory tracking in real-time.