Lu Jiawei, Liu Yueyue, Huang Wentao, Bi Kaitao, Zhu Yixin, Fan Qigao
College of Internet of Things Engineering, Jiangnan University, Wuxi 214000, China.
Cyborg Bionic Syst. 2022 Oct 21;2022:9835014. doi: 10.34133/2022/9835014. eCollection 2022.
Microrobots have great application potential in the biomedical field, to realize the precision and efficiency of microrobots in vivo is research focus in this field. Microrobots are accompanied by various disturbances in complex environment. These disturbances will affect the motion control of microrobots, resulting in the inability of the micromanipulation tasks to be completed effectively. To this end, a robust motion control method is proposed for precise path tracking of microrobots in this paper. The extended state observer (ESO) is used to estimate the total disturbances and uncertainties of the system. A path tracking controller is designed by combining sliding mode control (SMC) and disturbances compensation, which is used to eliminate the total disturbances of the system and realize the fast and accurate path tracking of microrobots. Finally, the path tracking experiments are implemented in the gradient magnetic field drive system. The experimental results show that the mean absolute error of the path tracking for microrobots in a simulated vascular structure is less than 14 m, and the root mean square error is less than 17 m by using the robust control method proposed in this paper. Compared with the traditional PID control method, it can better suppress external disturbances and uncertainties of the system and improve the path tracking accuracy of microrobots effectively. It shows stronger anti-interference ability and robustness.
微型机器人在生物医学领域具有巨大的应用潜力,实现微型机器人在体内的精确性和效率是该领域的研究重点。微型机器人在复杂环境中会受到各种干扰。这些干扰会影响微型机器人的运动控制,导致微操作任务无法有效完成。为此,本文针对微型机器人的精确路径跟踪提出了一种鲁棒运动控制方法。采用扩展状态观测器(ESO)估计系统的总干扰和不确定性。结合滑模控制(SMC)和干扰补偿设计了路径跟踪控制器,用于消除系统的总干扰,实现微型机器人的快速精确路径跟踪。最后,在梯度磁场驱动系统中进行了路径跟踪实验。实验结果表明,采用本文提出的鲁棒控制方法,微型机器人在模拟血管结构中的路径跟踪平均绝对误差小于14 m,均方根误差小于17 m。与传统的PID控制方法相比,它能更好地抑制系统的外部干扰和不确定性,有效提高微型机器人的路径跟踪精度。它显示出更强的抗干扰能力和鲁棒性。