A proposed soft pneumatic actuator control based on angle estimation from data-driven model
A proposed soft pneumatic actuator control based on angle estimation from data-driven model
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DOI：
10.1177/0954411920911277
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发表时间：
2020-03-17
期刊：
影响因子：
1.8
通讯作者：
Maged, Shady A.
中科院分区：
文献类型：
--
作者：
Mohamed, Mahmoud H.;Wagdy, Soha H.;Maged, Shady A.
本文提出了一种用于软气动执行器的弯曲角控制器，该控制器可应用于软机器人康复手套中，以帮助中风幸存者等手部损伤患者。当气动压力施加到执行器上时，使用数据驱动模型来估计角度。此外，还利用有限元模型对执行器的尺寸进行了手动优化。嵌入式FLEX传感器与定制测试台一起用于收集数据驱动模型的输入数据。这台钻机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。实验验证了模型的准确性以及修正后的比例-积分-微分控制器的角控制器性能。后一种控制器的设计目的是缓解电磁阀在不同执行器压力下的非线性响应。数据驱动模型和所使用的控制器允许更准确的估计和更快的响应。
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.