Adaptive Controller and Observer for a Magnetic Microrobot

Abstract

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.

Observer-based controller for microrobot in pulsatile blood flow

“…Proof: Properties (P1) and (P2) have been demonstrated in [15] and [20], respectively. In particular, the local controllability of system (7) is inherited from the controllability of its linearized time-variant system along the reference trajectory z ref (t) [21], [22].…”

Navigation of a rolling microrobot in cluttered environments for automated crystal harvesting

“…In our review of the literature, we only found two attempts at advanced kinematic path planning of untethered microrobots other than simple waypoint selection. The first is in [14], where an optimal path was generated to limit the control effort required to move a microrobot through pulsing blood flow. In [15], the fast marching method (FMM) was used to solve the path planning problem between a start and end position in a blood vessel.…”

“…In [20] time delay estimation (TDE) was used to account for uncertainty in parameters associated with nonlinear dynamics in the system model. In [14], nonlinear adaptive control was considered for a magnetically-pulled microrobot navigating through endovascular blood vessels. Backstepping was used to generate a control law that is Lyapunov-stable about a trajectory given linear uncertain parameters in the dynamics.…”

MRI-based dynamic tracking of an untethered ferromagnetic microcapsule navigating in liquid

“…A control module ( ) generates the magnetic gradient field to propel the microcarrier. Different control schemes have been sucessfully tested, such as a proportional-integral-derivative (PID) controller [15] , predictive controller [16] , or adaptive backstepping controller [17] . Moreover, the overall concept of the MRI-tracking system is based on the fact that both tracking and propulsion are possible with the manufacturer-supplied gradient coils of the MRI system.…”