基于输入-输出反馈线性化的软外指与人指离散非线性耦合动力学轨迹控制

Umme Kawsar Alam, Kassidy Shedd, M. Haghshenas-Jaryani
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引用次数: 1

摘要

本文提出了一种基于准静态模型的控制算法,用于控制具有三个独立驱动关节的软体机器人外指与人的手指物理交互的运动。建立了软体外指与人体手指模型之间物理相互作用的准静态分析模型。然后,将该模型表示为非线性离散多输入多输出(MIMO)状态空间表示,用于控制系统设计。利用输入-输出反馈线性化,设计控制输入对输入-输出进行线性化,其中输入为单个软执行器的驱动压力,输出为人体指尖的位姿。讨论了用于轨迹跟踪控制的非线性离散系统的渐近稳定性。采用软性机器人外骨骼手指(exo-digit)和集成IMU传感器的3d打印人体手指模型进行实验测试。开发了一种基于arduino的电气动控制硬件来控制软外指的驱动压力。通过仿真研究和实验测试,验证了该控制器在日常生活活动中跟随不同姿态轨迹的有效性。基于模型的控制器能够以非常低的平均均方根误差跟随所需的轨迹,x方向为2.27 mm, y方向为2.75 mm,人体手指远端连杆在z轴方向上的方向为3.90度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trajectory Control in Discrete-Time Nonlinear Coupling Dynamics of a Soft Exo-Digit and a Human Finger Using Input–Output Feedback Linearization
This paper presents a quasi-static model-based control algorithm for controlling the motion of a soft robotic exo-digit with three independent actuation joints physically interacting with the human finger. A quasi-static analytical model of physical interaction between the soft exo-digit and a human finger model was developed. Then, the model was presented as a nonlinear discrete-time multiple-input multiple-output (MIMO) state-space representation for the control system design. Input–output feedback linearization was utilized and a control input was designed to linearize the input–output, where the input is the actuation pressure of an individual soft actuator, and the output is the pose of the human fingertip. The asymptotic stability of the nonlinear discrete-time system for trajectory tracking control is discussed. A soft robotic exoskeleton digit (exo-digit) and a 3D-printed human-finger model integrated with IMU sensors were used for the experimental test setup. An Arduino-based electro-pneumatic control hardware was developed to control the actuation pressure of the soft exo-digit. The effectiveness of the controller was examined through simulation studies and experimental testing for following different pose trajectories corresponding to the human finger pose during the activities of daily living. The model-based controller was able to follow the desired trajectories with a very low average root-mean-square error of 2.27 mm in the x-direction, 2.75 mm in the y-direction, and 3.90 degrees in the orientation of the human finger distal link about the z-axis.
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