摘要
为解决外骨骼机器人在外界干扰与模型误差等不确定因素的影响下存在的轨迹跟踪控制准确性与稳定性不足等问题,提出一种基于Udwadia-Kalaba(U-K)理论的自适应鲁棒轨迹跟踪控制算法。首先,基于U-K理论相对简单地建立外骨骼机器人系统的运动方程,快速准确求解系统约束力;其次,针对系统不确定性因素设计自适应鲁棒控制器以保持系统的稳定性,并通过仿真验证了算法的可行性;最后,以基于二自由度外骨骼机器人进行对比实验,结果表明基于所提方法外骨骼两关节轨迹跟踪控制精度分别达到0.0148 rad和0.0251 rad,相比作为对照的PID控制算法提升了76.9%和60.0%,验证了该方法的有效性。
To address the insufficient accuracy and stability of trajectory tracking control in exoskeleton robots under uncertain factors such as external interference and model errors,an adaptive robust trajectory tracking control algorithm based on Udwadia-Kalaba(U-K)theory is proposed.Firstly,the motion equations of the exoskeleton robot system are established relatively simply based on the U-K theory,enabling fast and accurate calculation of system constraint forces.Secondly,an adaptive robust controller is designed to handle system uncertainties and maintain system stability.The feasibility of the algorithm is verified through simulations.Finally,comparative experiments are conducted using a two-degree-of-freedom exoskeleton robot.The results indicate that,with the proposed method,the trajectory tracking control accuracy of the two joints of the exoskeleton robot reaches 0.0148 rad and 0.0251 rad respectively,representing a 76.9%and 60.0%improvement compared to the PID control algorithm used as a control.This confirms the effectiveness of the proposed method.
作者
张名琦
沙连森
史文青
张文彬
黄锟
刘斌
ZHANG Mingqi;SHA Liansen;SHI Wenqing;ZHANG Wenbin;HUANG Kun;LIU Bin(School of Biomedical Engineering(Suzhou),Department of Life Science and Medicine,University of Science and Technology of China,Hefei 230000,China;Suzhou Institute of Biomedical Engineering and Technology,Chinese Academy of Sciences,Suzhou 215163,China)
出处
《组合机床与自动化加工技术》
北大核心
2025年第4期107-112,117,共7页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家重点研发计划资助项目(2020YFC2007402,2020YFC2007404,2020YFC2007401,2020YFC2007400,2020YFC2007403,2020YFC2007405,2022YFC2405603,2022YFC2405604)
江苏省科技计划项目资助项目(BE2021053,BE2021012,BE2021012-3,BE2021012-4,BE2022153,BE2022117)
苏州市基础研究试点项目(SJC2022011)
江苏省前沿引领技术基础研究专项项目(BK20192004C)。
