SMA驱动手指康复机器人模糊自适应控制方法研究  

Research on the fuzzy adaptive control method forSMA-driven finger rehabilitation robots

作　　者：王扬威 吕佩伦 郑舒方 王奔 WANG Yangwei;LYU Peilun;ZHENG Shufang;WANG Ben(College of Mechanical and Electrical Engineering,Northeast Forestry University,Harbin 150040,China)

机构地区：[1]东北林业大学机电工程学院,哈尔滨150040

出　　处：《重庆理工大学学报（自然科学）》2023年第2期316-323,共8页Journal of Chongqing University of Technology：Natural Science

基　　金：国家自然科学基金项目(52075089);黑龙江省自然科学基金项目(LH2019E008);。

摘　　要：针对形状记忆合金(shape memory alloy,SMA)丝驱动手指康复机器人弯曲角度难以精确控制的情况,提出一种模糊自适应PID控制算法,该方法基于手指康复机器人的运动学模型和合金丝驱动模型,利用电阻映射的弯曲角度反馈,采用模糊自适应参数实现位置控制。搭建手指康复机器人实验测试平台,分别采用传统PID和模糊自适应PID控制方法对食指进行位置控制实验,并分析稳定后食指各关节位置的控制效果。研究结果表明与传统PID控制算法相比,模糊自适应控制算法相比于PID控制达到角度稳态时间提高2~3 s,调节时间更短,位置误差2°,在外界扰动条件下能在3 s内完成自适应调节,具有较强的鲁棒性,能够更好地补偿SMA相变过程中的迟滞问题,证明了方法的有效性。Aiming at the problem that it is difficult to accurately control the bending angle of a finger rehabilitation robot driven by a shape memory alloy(SMA)wire,this paper proposes a fuzzy adaptive PID control algorithm.Based on the kinematics model and the alloy wire drive model of a finger rehabilitation robot,this method utilizes the bending angle feedback of resistance mapping and adopts fuzzy adaptive parameters to realize position control.An experimental test platform for finger rehabilitation robots is built,the traditional PID and fuzzy adaptive PID control methods are used to conduct position control experiments on the index finger,and position control effects of each index finger joint after stability are analyzed.The research results show that,compared with the traditional PID control algorithm,the fuzzy adaptive control algorithm takes 2~3 s longer to reach the angle steady state time,the adjustment time is shorter,the position error is 2°,and the adaptive adjustment can be completed within 3 s under external disturbance conditions.The proposed method has strong robustness and can better compensate the hysteresis in the SMA phase changing process,which proves its effectiveness.

关 键 词：手指康复机器人 形状记忆合金丝 模糊自适应 位姿控制 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]