Task-dependent controllers widely used in exoskeletons track predefined trajectories, which overly constrain the volitional motion of individuals with remnant voluntary mobility. Energy shaping, on the other hand, provides task-invariant assistance by altering the human body's dynamic characteristics in the closed loop. While human-exoskeleton systems are often modeled using Euler-Lagrange equations, in our previous work we modeled the system as a port-controlled-Hamiltonian system, and a task-invariant controller was designed for a knee-ankle exoskeleton using interconnection-damping assignment passivity-based control. In this paper, we extend this framework to design a controller for a backdrivable hip exoskeleton to assist multiple tasks. A set of basis functions that contains information of kinematics is selected and corresponding coefficients are optimized, which allows the controller to provide torque that fits normative human torque for different activities of daily life. Human-subject experiments with two able-bodied subjects demonstrated the controller's capability to reduce muscle effort across different tasks.
翻译:基于任务的控制器通常在外骨骼中被广泛使用来跟踪预定义的轨迹,这过度约束了病患带着残留的自愿活动的身体动向。而能量整形则通过在闭环中改变人体动力特性来提供任务不变的辅助作用。虽然人-外骨骼系统通常用欧拉-拉格朗日方程建模,但在我们之前的工作中,我们将系统建模为一个端口控制哈密顿系统,并使用互连阻尼分配基于从动性的控制设计了一种膝踝外骨骼的任务不变控制器。在本文中,我们将此框架扩展到设计一个可逆髋部外骨骼的控制器,以帮助多项任务。我们选择了一组包含运动学信息的基函数,并优化了相应的系数,从而使控制器能够为不同日常活动提供符合正常人肌肉扭矩的扭矩。两名健康志愿者参与的人类实验证明了该控制器在不同任务中降低肌肉力量的能力。