Simulation and optimization of Lower Limb Rehabilitation Exoskeleton based on Fuzzy PID control

As a new type of intelligent rehabilitation equipment for patients with lower limb motor dysfunction, lower limb rehabilitation exoskeleton robots have become a research hotspot in the field of rehabilitation medicine engineering worldwide. In response to the limitations of traditional PID control in complex human-computer interaction scenarios, such as weak anti-interference ability and difficult parameter tuning, this study innovatively proposes an adaptive PID control strategy based on fuzzy inference mechanism. By constructing a three-dimensional fuzzy rule library to achieve dynamic optimization of control parameters, a lower limb exoskeleton model was established in Adams and simulated in Matlab. Experimental verification showed that this algorithm reduces signal response time and significantly improves disturbance recovery speed compared to traditional PID, significantly improving system control accuracy and anti-interference ability. It provides reliable technical support for the clinical translation of lower limb rehabilitation robots.