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基于介电弹性体的软材料致动器自感知控制

Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers.

作者信息

Hoffstadt Thorben, Maas Jürgen

机构信息

Mechatronic System Laboratory, Institute of Machine Design and Systems Technology, Technische Universität Berlin, Berlin, Germany.

出版信息

Front Robot AI. 2019 Dec 13;6:133. doi: 10.3389/frobt.2019.00133. eCollection 2019.

Abstract

Due to their energy density and softness that are comparable to human muscles dielectric elastomer (DE) transducers are well-suited for soft-robotic applications. This kind of transducer combines actuator and sensor functionality within one transducer so that no external senors to measure the deformation or to detect collisions are required. Within this contribution we present a novel self-sensing control for a DE stack-transducer that allows to control several different quantities of the DE transducer with the same controller. This flexibility is advantageous e.g., for the development of human machine interfaces with soft-bodied robots. After introducing the DE stack-transducer that is driven by a bidirectional flyback converter, the development of the self-sensing state and disturbance estimator based on an extended Kalman-filter is explained. Compared to known estimators designed for DE transducers supplied by bulky high-voltage amplifiers this one does not require any superimposed excitation to enable the sensor capability so that it also can be used with economic and competitive power electronics like the flyback converter. Due to the behavior of this converter a sliding mode energy controller is designed afterwards. By introducing different feed-forward controls the voltage, force or deformation can be controlled. The validation proofs that both the developed self-sensing estimator as well as the self-sensing control yield comparable results as previously published sensor-based approaches.

摘要

由于介电弹性体(DE)换能器的能量密度和柔软度与人体肌肉相当,因此非常适合软机器人应用。这种换能器在一个换能器中结合了致动器和传感器功能,因此无需外部传感器来测量变形或检测碰撞。在本论文中,我们提出了一种用于DE叠层换能器的新型自感应控制方法,该方法允许使用同一个控制器来控制DE换能器的几个不同量。这种灵活性例如对于开发具有软体机器人的人机接口是有利的。在介绍了由双向反激变换器驱动的DE叠层换能器之后,解释了基于扩展卡尔曼滤波器的自感应状态和干扰估计器的开发。与为笨重的高压放大器供电的DE换能器设计的已知估计器相比,该估计器不需要任何叠加激励来实现传感器功能,因此它也可以与经济且有竞争力的电力电子设备(如反激变换器)一起使用。由于该变换器的特性,随后设计了一种滑模能量控制器。通过引入不同的前馈控制,可以控制电压、力或变形。验证证明,所开发的自感应估计器和自感应控制产生的结果与先前发表的基于传感器的方法相当。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b43/7805669/e013fe547d07/frobt-06-00133-g0001.jpg

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