Research on Coordinated Control of Load-bearing Gait of Firefighter Lower Limb Exoskeleton Based on Fuzzy PID
Year: 2026
Type: conference-paper
Abstract: Fire rescue operations have characteristics of high load, strong disturbance, and variable working conditions. After firefighters wear the complete protective and rescue equipment, their overall load can reach 25 to 45 kg. Long-term walking with heavy load can easily cause fatigue in lower limb muscles and joint damage, severely restricting the efficiency and safety of rescue operations. However, the human-machine coupling system under different load levels presents strong nonlinearity, inertia time-varying, and significant load disturbance characteristics, which pose significant challenges to high-precision gait tracking and human-machine compliant collaborative control. The traditional fuzzy PID control in the field of exoskeleton trajectory tracking is mostly applicable to rehabilitation and industrial fixed-load scenarios, and cannot be adapted to the exclusive working conditions of fire-fighting with graded heavy loads and human-machine flexible coupling. This paper innovatively focuses on three directions: modeling of fire-fighting graded centralized loads, multi-load multi-dimensional evaluation system, and optimization of fuzzy rules PID for heavy-load adaptation, to conduct research. This paper takes the fire leg exoskeleton as the research object, considering the typical load gradient conditions of firefighting, and establishes a multi-body dynamic model of human-exoskeleton coupling in the sagittal plane. The fuzzy PID adaptive control strategy is adopted, with joint angle tracking error and error change rate as inputs, and the PID control parameters are self-tuned online through fuzzy reasoning rules to achieve adaptive tracking of the four-joint hip joint and knee joint gait trajectories. The simulation results show that the designed fuzzy PID controller can adaptively match the dynamic parameter perturbations brought by different loads, and the hip joint maintains high-precision steady-state tracking throughout the process. As the load level increases, the overall tracking error of the system grows gradually, and the controller has excellent load robustness and condition self-adaptation ability, with small human-machine interaction force fluctuations and good collaborative compliance. This research can provide simulation support and theoretical reference for the design of intelligent controllers for fire leg exoskeletons and the collaborative control of variable loads in gait.
Authors: Shichao Kuai, Wei Zheng
Institution: Shenyang Fire Research Institute
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7204466353