Adaptive backstepping and MEMS force sensor for an MRI-guided microrobot in the vasculature
A microrobot consisting of a polymer binded aggregate of ferromagnetic particles is controlled using aMagnetic Resonance Imaging (MRI) device in order to achieve targeted therapy. The primary contribution of this paper is the design of an adaptive backstepping controller coupled with a high gain observer based on a nonlinear model of a microrobot in a blood vessel. This work is motivated by the difficulty in accurately determining many biological parameters, which can result in parametric uncertainties to which model-based approaches are highly sensitive. We show that the most sensitive parameter, magnetization of the microrobot, can be measured using a Micro-Electro-Mechanical Systems (MEMS) force sensor, while the second one, the dielectric constant of blood, can be estimated on line. The efficacy of this approach is illustrated by simulation results.
Laurent Arcese Matthieu Fruchard Felix Beyeler Antoine Ferreira Bradley J. Nelson
Laboratoire PRISME,Universit(e) dOrl(e)ans,IUT de Bourges 63 Av de Lattre de Tassigny,18020,Bourges FemtoTools GmbH,ETHZ-IRIS,Tannenstrasse 3,CH-8092,Zurich,Switzerland Laboratoire PRISME,Universit(e) dOrl(e)ans,ENSI de Bourges 88 Bd Lahitolle,18000,Bourges,France Institute of Robotics and Intelligent Systems,ETH Zurich,Tannenstrasse 3,CH-8092,Zurich,Switzerland
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
4121-4126
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）