Remote Magnetic Levitation Using Reduced Attitude Control and Parametric Field Models

View at publisher
Authors: Neelaksh Singh, Jasan Zughaibi, Denis von Arx, Bradley J. Nelson, Michael Muehlebach
Cited by: 1
References: 45

Abstract

Electromagnetic navigation systems (eMNS) are increasingly used in minimally invasive procedures such as endovascular interventions and targeted drug delivery due to their ability to generate fast and precise magnetic fields. In this paper, we utilize the OctoMag and a custom 13-coil eMNS to achieve remote levitation and control of multiple rigid bodies across large air gaps, showcasing the dynamic capabilities of such systems. A compact parametric analytical model maps coil currents to the forces and torques acting on the levitating object, eliminating the need for computationally expensive simulations or lookup tables and establishing a levitator- and platform-agnostic control framework. Translational motion is stabilized using linear quadratic regulators. A nonlinear time-invariant controller is used to regulate the reduced attitude accounting for the inherent uncontrollability of rotations about the dipole axis and stabilizing the full five degrees of freedom controllable pose subspace. We analyze key design limitations and evaluate the approach through trajectory tracking experiments across different objects and actuation platforms. Notably, our proposed controller demonstrates superiority over an equivalent baseline PID formulation, reliably tracking large spatial angles up to 65$^\circ$. This work demonstrates the dynamic capabilities and potential of feedback control in electromagnetic navigation, which is likely to open up new medical applications.

Fields of Study & Subjects

Magnetic Bearings and Levitation Dynamics Inertial Sensor and Navigation Geomagnetism and Paleomagnetism Studies

Publication details

Journal / source
IEEE Robotics and Automation Letters
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
11
Issue
7
Pages
8028–8035
Publication date
11 May 2026