Nanorobotics pp 243-273 | Cite as

Propulsion and Navigation Control of MRI-Guided Drug Delivery Nanorobots

  • Laurent Arcese
  • Matthieu Fruchard
  • Antoine Ferreira


The present chapter discusses the control design of MRI-guided robots in the vasculature to achieve targeted therapy through precise drug delivery. Such robots consist of a polymer-binded aggregate of nanosized ferromagnetic and drug particles that can be propelled by the gradient coils of an MRI device. The feasibility of the concept has been largely studied in the literature, but few works address the nonlinear control issues related to a fine modeling of the forces acting on the robot. Different solutions have been proposed for the design of a microrobot, and the principal ones are here exposed. In this chapter, a fine modeling is developed with concerns about the constraints of the application. The notion of optimal trajectory derived from the nonlinear model is presented and shows that one can exploit the complexity of such a model to optimize the tracking performances. The design of a Lyapunov controller is addressed, with the synthesis of an adaptive backstepping law that ensures a fine tracking despite some modeling errors and estimates some key uncertain physiological parameters. The design of a nonlinear observer for reconstructing the robot’s unmeasured velocity is also exposed. The benefits of this fine modeling and the use of advanced control law and observer are illustrated by simulations. Finally, perspectives and open problems in the field of MRI-guided robots’ control are discussed.


Drag Force Reference Trajectory Gradient Coil Actuator Saturation Magnetic Gradient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by European Union’s 7th Framework Program and its research area ICT-2007. 3. 6 Micro/nanosystems under the project NANOMA (Nano-Actuactors and Nano-Sensors for Medical Applications).


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Copyright information

© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  • Laurent Arcese
    • 1
  • Matthieu Fruchard
    • 1
  • Antoine Ferreira
    • 2
  1. 1.Laboratoire PRISMEUniversity of OrleansBourges cedexFrance
  2. 2.Laboratoire PRISMEUniversity of Orleans, ENSI de BourgesBourgesFrance

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