Gunderman Anthony L, Azizkhani Milad, Sengupta Saikat, Cleary Kevin, Chen Yue
Department of Biomedical Engineering, Georgia Institute of Technology/Emory, Atlanta, GA 30338 USA.
Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232 USA.
IEEE ASME Trans Mechatron. 2024 Jun;29(3):1714-1725. doi: 10.1109/tmech.2023.3329296. Epub 2023 Dec 13.
Magnetic resonance (MR) conditional actuators and encoders are the key components for MR-guided robotic systems. In this article, we present the modeling and control of our MR-safe pneumatic radial inflow motor and encoder. A comprehensive model is developed that considers the primary dynamic elements of the system, including: 1) motor dynamics, 2) pneumatic transmission line dynamics, and 3) valve dynamics. After model validation, we present a simplified third order model that facilitates design of a first order sliding mode controller (TO-SMC). Finally, the motor hardware is tested in a 7T MRI. No image distortion or artifacts were observed. We posit the MR-safe motor and dynamic model will lower the entry barriers for researchers interested in MR-guided robots and promote wider adoption of MR-guided robotic systems.
磁共振（MR）条件驱动装置和编码器是MR引导机器人系统的关键组件。在本文中，我们介绍了我们的MR安全气动径向流入电机和编码器的建模与控制。我们开发了一个综合模型，该模型考虑了系统的主要动态元件，包括：1）电机动力学，2）气动传输线动力学，以及3）阀门动力学。在模型验证之后，我们提出了一个简化的三阶模型，该模型有助于设计一阶滑模控制器（TO-SMC）。最后，在7T磁共振成像仪中对电机硬件进行了测试。未观察到图像失真或伪影。我们认为，MR安全电机和动态模型将降低对MR引导机器人感兴趣的研究人员的进入门槛，并促进MR引导机器人系统的更广泛应用。
