Abstract-This paper deals with the benefits of using a nonlinear model-based approach for controlling magnetically guided therapeutic microrobots in the cardiovascular system. Such robots used for minimally invasive interventions consist of a polymer binded aggregate of nanosized ferromagnetic particles functionalized by drug-conjugated micelles. The proposed modeling addresses wall effects (blood velocity in minor and major vessels' bifurcations, pulsatile blood flow and vessel walls, and effect of robot-to-vessel diameter ratio), wall interactions (contact, van der Waals, electrostatic and steric forces), nonNewtonian behaviour of blood and different driving designs as well. Despite nonlinear and thorough, the resulting model can both be exploited to improve the targeting ability and be controlled in closed-loop using nonlinear control theory tools. In particular, we infer from the model an optimization of both the designs and the reference trajectory to minimize the control efforts. Efficiency and robustness to noise and model parameter's uncertainties are then illustrated through simulations results for a bead pulled robot of radius 250µm in a small artery.Index Terms-Endovascular navigation, magnetic steering, nonlinear modeling, optimal trajectory, nonlinear controller and observer.

International audienceThis review presents the state of the art of magnetic resonance imaging(MRI)-guided nanorobotic systems that can perform diagnostic, curative,and reconstructive treatments in the human body at the cellular and subcellular levels in a controllable manner. The concept of an MRI-guided nanorobotic system is based on the use of an MRI scanner to induce the required external driving forces to propel magnetic nanocapsules to a specific target. It is an active targeting mechanism that provides simultaneous propulsion and imaging capabilities, which allow the implementation of real-time feedback control of the targeting process. The architecture of the system comprises four main modules: (a) the nanocapsules, (b) the MRI propulsion module, (c) theMRI trackingmodule (for image processing), and (d ) the controller module. A key concept is the nanocapsule technology, which is based on carriers such as liposomes, polymermicelles, gold nanoparticles, quantum dots, metallic nanoshells, and carbon nanotubes. Descriptions of the significant challenges faced by theMRI-guided nanorobotic system are presented, and promising solutions proposed by the involved research community are discussed. Emphasis is placed on reviewing the limitations imposed by the scaling effects that dominate within the blood vessels and also on reviewing the control algorithms and computational tools that have been developed for real-time propulsion and tracking of the nanocapsules

Abstract-The present paper discusses the control design of a magnetically-guided microrobotic system in blood vessels to perform minimally invasive medical procedures. Such microrobots consist of a polymer binded aggregate of nanosized ferromagnetic particles and a possible payload that can be propelled by the gradient coils of a magnetic device. A fine modeling is developed and used to define an optimal trajectory which minimizes the control efforts. We then synthesize an adaptive backstepping law that ensures a Lyapunov stable and fine tracking despite modeling errors and estimates some key uncertain parameters. As the controller synthesis uses the microrobot unmeasured velocity, the design of a high gain observer is also addressed. Simulations and experiment illustrate the robustness to both noise measurement and some uncertain physiological parameters for a 250µm radius microrobot navigating in a fluidic environment.Index Terms-Magnetic microrobot, nonlinear modeling, adaptive backstepping, high gain observer, noise and parametric uncertainties.

A general framework for the feedback control of mobile manipulators is proposed. Its main originality lies in its capacity to address in a unified manner both cases of omnidirectional and nonholonomic mobile platforms. It also allows for the execution of the desired manipulation task without the manipulator colliding into its joint limits, whenever these two objectives are compatible. This is obtained without having to rely upon trajectory planning. In the nonholonomic case this feature, which is not demonstrated for previous feedback control schemes proposed in the literature, is instrumental for performing reflex maneuvers automatically. It relies upon the concept, used in the control design, of a companion omnidirectional frame associated with the physical platform. The generality of the approach can be appreciated from its applicability to various nonholonomic platforms, for example unicycle-type and car-like.

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Abstract-This paper reports the use of a MRI device to pull a magnetic microrobot inside a vessel and control its trajectory. The bead subjected to magnetic and hydrodynamic forces is first modeled as a nonlinear control system. Then, a backstepping approach is discussed in order to synthesize a feedback law ensuring the stability along the controlled trajectory. We show that this control law, combined with a high gain observer, provides good tracking performances and robustness to measurement noise as well as to some matched uncertainties.

The paper addresses the 2D observer-based control of a magnetic microrobot navigating in a cylindrical blood vessel along a reference trajectory. In particular, this robot faces the nonlinear drag force induced by the pulsatile blood flow, which can hardly be measured. Consequently, a mean value theorem (MVT) based observer to estimate the blood velocity from the sole measurement of the robot position is proposed. Also, the stability of the observer-based backstepping controller is proved. The resulting estimation and tracking are then illustrated through simulations, as well as robustness to parametric uncertainty, measurement noise, and dynamical errors when the pulsatile blood flow is incorrectly modeled.

Abstract-A microrobot consisting of a polymer binded aggregate of ferromagnetic particles is controlled using a Magnetic 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.