重庆大学 机械与运载工程学院，重庆 400044
黄国勤（1976—），男，副教授，博士，主要从事流体传动与智能控制、机器人技术研究，（E-mail） huangguoqin@cqu.edu.cn。
TP242
国家重点研发计划资助项目（2019YFB1703600）；国家自然科学基金资助项目（62033001）。
College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, P. R. China
Supported by National Key R&D Program of China (2019YFB1703600), and National Natural Science Foundation of China (62033001).
为了解决气动人工肌肉驱动的下肢康复机器人轨迹跟踪中存在外界干扰和系统参数不确定的问题，提出了一种关节控制自抗扰算法。该方法在气动人工肌肉关节伺服控制系统数学模型基础上，通过三阶状态扩张观测器对系统状态及系统干扰进行估计，对干扰进行实时补偿，并基于分离性原理进行参数整定；利用气动人工肌肉试验平台对控制系统进行定角度条件下的阶跃信号跟踪控制、方波跟踪控制和正弦跟踪控制对比验证实验。实验结果表明：所设计的自抗扰控制器较比例-积分-微分（proportion integration differentiation，PID）控制器响应时间更快、控制误差更低，满足下肢康复机器人的应用控制要求。
To solve the problems of external interference and system parameter uncertainty in the trajectory tracking of a lower limb rehabilitation robot driven by pneumatic artificial muscles, an active disturbance rejection algorithm for joint control is proposed. Based on the mathematical model of the servo control system of the pneumatic artificial muscle joint, the method firstly estimates the system state and disturbance using a third-order state expansion observer. It then compensates for the disturbance in real time and adjusts the parameters based on the separation principle. Subsequently, with using a pneumatic artificial muscle test platform, the step signal tracking control, square wave tracking control, and sine tracking control of the control system are compared and verified under fixed angle conditions. Experimental results show that the designed active disturbance rejection control (ADRC) has a faster response time and lower control error than the proportional integral differential (PID)controller, meeting the application control requirements of the lower limb rehabilitation robot.
黄国勤,米俊丞,左思红.基于气动肌肉驱动的关节自抗扰控制[J].重庆大学学报,2024,47(9):51-60.
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