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基于自抗扰控制器的血管介入主从式手术机器人系统控制方法

ADRC-Based Control Method for the Vascular Intervention Master-Slave Surgical Robotic System.

作者信息

Zhou Wei, Guo Shuxiang, Guo Jin, Meng Fanxu, Chen Zhengyang

机构信息

School of Life Science, Beijing Institute of Technology, Beijing 100081, China.

Key Laboratory of Convergence Medical Engineering System and Healthcare Technology, Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing 100081, China.

出版信息

Micromachines (Basel). 2021 Nov 25;12(12):1439. doi: 10.3390/mi12121439.

Abstract

In vascular interventional surgery, surgeons operate guidewires and catheters to diagnose and treat patients with the assistance of the digital subtraction angiography (DSA). Therefore, the surgeon will be exposed to X-rays for extended periods. To protect the surgeon, the development of a robot-assisted surgical system is of great significance. The displacement tracking accuracy is the most important issue to be considered in the development of the system. In this study, the active disturbance rejection control (ADRC) method is applied to guarantee displacement tracking accuracy. First, the core contents of the proportional-integral-derivative (PID) and ADRC methods are analyzed. Second, comparative evaluation experiments for incremental PID and ADRC methods are presented. The results show that the ADRC method has better performance of than that of the incremental PID method. Finally, the calibration experiments for the ADRC control method are implemented using the master-slave robotic system. These experiments demonstrate that the maximum tracking error is 0.87 mm using the ADRC method, effectively guaranteeing surgical safety.

摘要

在血管介入手术中,外科医生在数字减影血管造影(DSA)的辅助下操作导丝和导管来诊断和治疗患者。因此,外科医生将长时间暴露在X射线下。为了保护外科医生,开发机器人辅助手术系统具有重要意义。位移跟踪精度是系统开发中要考虑的最重要问题。在本研究中,应用自抗扰控制(ADRC)方法来保证位移跟踪精度。首先,分析了比例积分微分(PID)和ADRC方法的核心内容。其次,给出了增量式PID和ADRC方法的对比评估实验。结果表明,ADRC方法比增量式PID方法具有更好的性能。最后,使用主从机器人系统对ADRC控制方法进行了校准实验。这些实验表明,使用ADRC方法时最大跟踪误差为0.87毫米,有效保证了手术安全。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/facd/8707856/bc2b9c195f3a/micromachines-12-01439-g001.jpg

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