The rehabilitation training of patients with lower limb motor dysfunction highly relies on the precise control of biomimetic knee joint robots. Existing control strategies generally suffer from insufficient control accuracy and weak anti-interference ability, and an optimization plan that balances high precision and strong anti-interference has not yet been formed, which seriously affects the effectiveness of rehabilitation training. In order to improve the control accuracy and anti-interference ability of biomimetic knee joint robots for leg rehabilitation training of patients with lower limb movement disorders, the purpose of this study is to address the performance shortcomings of existing biomimetic knee joint robot control strategies. The goal is to propose a high-precision and strong anti-interference control strategy to provide more reliable rehabilitation support for patients with lower limb movement disorders. Therefore, this article proposes an optimization strategy based on the Spider Bee Algorithm (SWO) combined with fuzzy PID control. Based on a biomimetic knee joint robot model, this study simulates three common pathological states of knee joint ligament injury, meniscus injury, and muscle atrophy in patients, and compares the trajectory tracking and anti-interference performance of PID, fuzzy PID, and SWO fuzzy PID control strategies. The experimental results show that the SWO fuzzy PID control strategy has the best comprehensive performance: the overshoot of knee joint angle control is only 9.7%, and the peak angle error is reduced to 2.1948°; when simulating pathological conditions, the system takes the shortest time to recover stability: 1.068 s for ligament injuries and 0.929 s for meniscus injuries, with maximum response errors below 0.017°. Simulation experiments on healthy subjects showed that the system had a tracking error of ≤5° under two rehabilitation training modes, meeting clinical accuracy requirements, and had good performance in restoring stability under irregular vibration interference. The core contribution of this study is the proposal of the SWO fuzzy PID optimization control strategy, which effectively addresses the shortcomings of existing strategies and significantly improves the control accuracy and anti-interference ability of bionic knee joint robots, providing theoretical support and practical reference for the application of bionic knee joint robots.
Li et al. (Tue,) studied this question.