摘要
为克服传统颈椎牵引康复方法个体差异适应能力弱、控制精度不足及难以动态调控等问题,文章基于自研的6-UPS并联结构颈椎康复机器人,提出了一种模糊PID位置控制方案。该机器人通过六个电动推杆实现多自由度牵引与姿态调节,为不同颈部节段和肌肉群提供多角度、多模式的康复训练。首先,在分析直流电机与丝杠传动的非线性耦合基础上,建立了单电动推杆系统的数学模型并推导出其传递函数;随后,将模糊逻辑嵌入PID框架中,通过在线自整定PID参数,有效应对因患者生理差异及时变负载等带来的不确定性与非线性;最后,利用Simulink与Fuzzy工具进行仿真验证,结果显示模糊PID控制器相比传统PID可明显缩短上升时间(0.141 s)与调整时间(0.236 s),且几乎无超调,有助于确保多自由度并联牵引在复杂工况下的快速性与稳定性。该研究为新型颈椎康复机器人的高精度与高适应性控制提供了有效的技术支撑,并为后续实现多自由度力位耦合及临床应用奠定了良好基础。
To address the limitations of traditional cervical traction rehabilitation methods,including poor adaptability to individual differences,insufficient control accuracy,and difficulty in dynamic regu-lation,this paper proposes a fuzzy PID position control scheme based on a self-developed 6-UPS parallel-structure cervical rehabilitation robot.This robot utilizes six electric linear actuators to achieve multi-degree-of-freedom traction and posture adjustment,providing multi-angle and multi-mode rehabilitation training for different cervical segments and muscle groups.First,a mathematical model of a single electric actuator system is established,and its transfer function is derived based on an analysis of the nonlinear coupling between the DC motor and the lead screw transmission.Then,fuzzy logic is embedded within the PID framework to enable online self-tuning of PID param-eters,effectively addressing uncertainties and nonlinearities caused by patient-specific physiolog-ical differences and time-varying loads.Finally,simulations are conducted using Simulink and the Fuzzy tool.The results demonstrate that,compared with conventional PID control,the fuzzy PID controller significantly reduces the rise time(0.141 s)and settling time(0.236 s)while exhibiting almost no overshoot.This improvement enhances the speed and stability of multi-degree-of-free-dom parallel traction under complex working conditions.This study provides an effective technical foundation for high-precision and highly adaptive control of next-generation cervical rehabilitation robots,laying the groundwork for future multi-degree-of-freedom force-position coupling control and clinical applications.
作者
刘辰旭
王晴晴
石萍
Chenxu Liu;Qingqing Wang;Ping Shi(School of Health Science and Engineering,University of Shanghai for Science and Technology,Shanghai)
出处
《建模与仿真》
2025年第5期868-878,共11页
Modeling and Simulation
