Dai Zhenhao, Rao Jinjun, Xu Zili, Lei Jingtao
School of Mechanical and Electrical Engineering and Automation, Shanghai University, Shanghai 200444, China.
Micromachines (Basel). 2022 May 26;13(6):827. doi: 10.3390/mi13060827.
Using the skeletal structure and muscle distribution of the hind limbs of a jumping kangaroo as inspiration, a bionic jumping leg was designed with pneumatic artificial muscles (PAMs) as actuators. Referring to the position of biarticular muscles in kangaroos, we constructed a bionic joint using biarticular and monoarticular muscle arrangements. At the same time, the problem of the joint rotation angle limitations caused by PAM shrinkage was solved, and the range of motion of the bionic joint was improved. Based on the output force model of the PAM, we established a dynamic model of the bionic leg using the Lagrange method. In view of the coupling problem caused by the arrangement of the biarticular muscle, an extended state observer was used for decoupling. The system was decoupled into two single-input and single-output systems, and angle tracking control was carried out using active disturbance rejection control (ADRC). The simulation and experimental results showed that the ADRC algorithm had a better decoupling effect and shorter adjustment time than PID control. The jumping experiments showed that the bionic leg could jump with a horizontal displacement of 320 mm and a vertical displacement of 150 mm.
以跳跃袋鼠后肢的骨骼结构和肌肉分布为灵感,设计了一种以气动人工肌肉(PAMs)为驱动的仿生跳跃腿。参照袋鼠中双关节肌肉的位置,我们采用双关节和单关节肌肉排列构建了一个仿生关节。同时,解决了由PAM收缩引起的关节旋转角度限制问题,提高了仿生关节的运动范围。基于PAM的输出力模型,我们使用拉格朗日方法建立了仿生腿的动力学模型。针对双关节肌肉排列引起的耦合问题,采用扩张状态观测器进行解耦。将系统解耦为两个单输入单输出系统,并采用自抗扰控制(ADRC)进行角度跟踪控制。仿真和实验结果表明,与PID控制相比,ADRC算法具有更好的解耦效果和更短的调节时间。跳跃实验表明,仿生腿能够实现水平位移320毫米、垂直位移150毫米的跳跃。