基于柔性驱动关节的下肢外骨骼双模态切换控制

Double-mode Switching Control of a Lower Limb Exoskeleton Based on Flexible Drive Joint

为了提高外骨骼关节柔性以及穿戴舒适性,设计了基于柔性驱动关节的可穿戴式下肢外骨骼,同时针对下肢外骨骼在控制的不同相位阶段其侧重点不同的特点,提出基于双模态切换的混合控制策略。首先,针对下肢外骨骼关节的柔性问题,设计了基于双平行弹簧的串联弹性体,并将其安装于外骨骼关节驱动模块,通过双编码器实现关节力矩和位置信息的反馈。然后,分析外骨骼在不同步态相位的运动特征,提出了双模态切换控制策略,即支撑相采用自适应阻抗控制算法来提高稳定性和抗冲击能力,摆动相采用自抗扰-终端滑模控制算法来提高响应速度和跟踪精度。最后,通过控制仿真和主被动跟踪实验,验证了本文算法相较于传统PID(比例-积分-微分)和自抗扰控制算法的优越性。被动跟踪实验结果说明当关节误差收敛范围在±5%时,收敛时间可达0.28 s;在主动跟踪实验中,实验人员穿戴外骨骼时髋关节和膝关节最大均方根误差分别为0.47°和1.28°,说明本文控制算法可以实时跟踪人体运动意图,满足人机交互柔顺性需求。

In order to improve the flexibility and wearability of exoskeleton, a wearable lower limb exoskeleton based on the flexible drive joint is designed. In view of the different focus points at different phases in the control of lower limb exoskeleton, a hybrid control strategy based on dual-mode switching is proposed. Firstly, a series elastomer based on double parallel springs is designed to solve the flexibility problem of the lower limb exoskeleton joint, and it is installed in the drive module of exoskeleton joint. The feedback of joint torque and position information is achieved through two encoders.Then, a dual-mode switching control strategy is proposed by analyzing the movement characteristics of the exoskeleton at different gait phases. The adaptive impedance control algorithm is adopted at the stance phase to improve stability and impact resistance, and the active disturbance rejection and fast terminal sliding mode control algorithm is adopted at the swing phase to improve response speed and tracking accuracy. Finally, control simulation and active-passive tracking experiments are carried out to verify the superiority of the proposed algorithm to traditional PID(proportional-integral-derivative) and active disturbance rejection control algorithms. The results of passive tracking experiment show that the convergence time can reach 0.28 s when the convergence range of joint error is ±5%. In the active tracking experiment, the maximum RMSEs(root mean squared errors) of the hip and knee joints are 0.47° and 1.28°respectively while the experimenters wear the exoskeleton.These experimental results show that the human movement intention can be tracked in real time by the proposed control algorithm, and the requirements for human-machine interaction flexibility are satisfied.