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1. Noncontact Planar Manipulation of Magnetic Particles by Minimum Number of Electromagnets

   https://doi.org/10.1109/CCTA62090.2026.11684067  

   Hasan, MD Nazmul; Komaee, Arash (August 2026, IEEE)

   This paper considers the noncontact manipulation of a magnetic particle inside a planar workspace encircled by an array of 3 electromagnets, the minimum number that allows for unconstrained planar manipulation of the particle. Since the size, weight, and cost of a magnetic manipulator directly depend on the number of its magnets, minimizing this number is highly desirable. Yet, magnetic manipulation with a minimum number of magnets exhibits certain limitations, which are investigated in this paper. It is shown both analytically and by experiment that while planar magnetic manipulation is feasible by an array of 3 electromagnets, it is less effective than what can be achieved by a larger number of magnets in terms of energy efficiency and the size of region in which magnetic manipulation is possible. 

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2. Robust Feedback Linearization for Noncontact Manipulation of Magnetic Particles by a Hexagonal Array of Electromagnets

   https://doi.org/10.1109/CASE58245.2025.11164149  

   Hasan, MD Nazmul; Komaee, Arash (August 2025, IEEE)

   This paper develops a robust feedback control law for planer steering of magnetic particles in a circular workspace using a hexagonal arrangement of electromagnets encircling the workspace. The electromagnets are actuated independently by a feedback loop to control their aggregate magnetic field flexibly, which is then exploited to exert magnetic force on the particles as needed for steering them along desired reference trajectories. This magnetic force is a highly nonlinear function of both the position of magnetic particles and the control voltages actuating the electromagnets. The control strategy in this work is to cancel this nonlinearity using a nonlinear inverse map, which in effect, realizes the concept of feedback linearization. Such an inverse map is developed in this paper in a specific way that drastically enhances its robustness against inherent modeling errors and uncertainty in the magnetic field. The resulting robust inverse map notably improves the performance of feedback control, as demonstrated by experiments in this paper. 

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3. Noncontact Manipulation of Magnetic Objects with an Array of Permanent Magnets and Linear Servomotors

   https://doi.org/10.1109/AIM55361.2024.10637208  

   Ekanayake, Lahiru; Madhusanka, Janaka; Komaee, Arash (July 2024, IEEE)

   This paper presents the concept, implementation, feedback control, and experimental verification of a noncontact magnetic manipulator that relies on a controllable array of permanent magnets to manipulate magnetized objects inside a workspace encircled by the magnets. To gain control over the aggregate magnetic field inside the workspace, the position of each magnet is independently controlled by a linear servomotor that dynamically changes the distance between that magnet and the workspace. By feedback control of the array of servomotors, the magnetic force applied to a magnetized object inside the workspace is dynamically adjusted to steer it along a desired reference trajectory. The successful steering of a small magnetic bead is demonstrated by experiments performed on a planar magnetic manipulator, designed and prototyped with six linear servomotors and six permanent magnets. 

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4. Magnetic Levitation Using Permanent Magnets: System Design, Feedback Stabilization, and Experimental Validation

   https://doi.org/10.1109/AIM55361.2024.10637103  

   Basnet, Dhiraj; Komaee, Arash (July 2024, IEEE)

   This paper presents the design, implementation, feedback stabilization, and experimental validation of a novel permanent magnet levitation system. Conventionally, magnetic levitation systems utilize electromagnets to levitate magnetic objects against gravity by stabilizing them around equilibrium points at which the applied magnetic force balances the gravity. This magnetic force must be dynamically adjusted by means of a stabilizing feedback loop, which is established by easy control of the electromagnet voltage. Despite the key advantage of easier control, electromagnets often produce much weaker magnetic forces compared to permanent magnets of similar size, weight, and cost. Therefore, this paper proposes the use of a permanent magnet to produce the magnetic force necessary for levitation, and the use of a linear servomotor to control the magnitude of this force by adjusting the distance between the magnet and the levitating object. To demonstrate this idea in practice, an experimental setup is designed, prototyped, and successfully stabilized using a computer-based feedback control loop. 

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5. Homotopy Continuation for Feedback Linearization of Noncontact Magnetic Manipulators

   https://doi.org/10.23919/ACC45564.2020.9147681  

   Riahi, Nayereh; Tituana, Luis R.; Komaee, Arash (July 2020, 2020 American Control Conference (ACC))

   null (Ed.)

   Magnetic fields render a unique ability to control magnetic objects without a direct mechanical contact. To exploit this potential for a broad range of medical, microrobotics, and microfluidics applications, noncontact magnetic manipulators have been designed using both electromagnets and permanent magnets. By feedback control of these manipulators, magnetic objects can be precisely driven in the directions required by an application of interest. The feedback design process for these manipulators is normally complicated by their highly nonlinear nature, particularly for those utilizing permanent magnets. Yet, feedback linearization techniques can be applied to compensate for the nonlinear nature of most magnetic manipulators. This goal can be achieved by solving an underdetermined system of nonlinear algebraic equations. This paper adopts a homotopy continuation approach to solve this system of equations. It is shown by simulations that the proposed feedback linearization scheme drastically improves the control performance compared to the alternative control design methods used in prior work. 

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