Advansys ESC, Cairo, Egypt.
Valeo Egypt (VIAS), Cairo, Egypt.
Proc Inst Mech Eng H. 2020 Jun;234(6):612-625. doi: 10.1177/0954411920911277. Epub 2020 Mar 17.
This article proposes a bending angle controller for soft pneumatic actuators, which could be implemented in soft robotic rehabilitation gloves to assist patients with hand impairment, such as stroke survivors. A data-driven model is used to estimate the angle as pneumatic pressure is applied to the actuator. Furthermore, a finite element model was used to manually optimize the dimensions of the actuator. An embedded flex sensor, which together with a custom testing rig, was used to gather input data for the data-driven model. This rig contains a pneumatic pressure control circuit as well as a camera for image acquisition. Collected data were fed into a linear regression model to predict the data-driven model. Experiments were carried out to validate model's accuracy as well as modified proportional-integral-derivative controller angle controller performance. The latter controller is designed to mitigate the non-linear response of solenoid valves at different pressures of the actuator. The data-driven model along with the used controller allows more accurate estimation and quicker response.
本文提出了一种用于软气动执行器的弯曲角度控制器，可将其应用于软机器人康复手套中，以帮助手部受损的患者，如中风幸存者。使用数据驱动模型来估计角度，因为气动压力施加到执行器上。此外，使用有限元模型手动优化执行器的尺寸。嵌入式挠曲传感器与定制的测试台一起用于为数据驱动模型收集输入数据。该测试台包含一个气动压力控制电路和一个用于图像采集的摄像头。收集的数据被输入到线性回归模型中，以预测数据驱动模型。进行了实验以验证模型的准确性以及改进的比例积分微分控制器角度控制器性能。后者的控制器旨在减轻在执行器的不同压力下电磁阀的非线性响应。数据驱动模型以及所使用的控制器允许更准确的估计和更快的响应。
