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1. Feedback Stabilization of a Permanent Magnet Levitation System

   https://doi.org/10.23919/ACC53348.2022.9867393  

   Shariatmadari, M. Reza; Komaee, Arash (June 2022, 2022 American Control Conference (ACC))

   A magnetic levitation system consists of a magnet facing groundward to attract a magnetic object against gravity and levitate it at a distance from the face of magnet. Due to the unstable nature of this system, it must be stabilized by means of feedback control, which adjusts the magnetic force applied to the levitating object depending on its measured position and possibly velocity. Conventionally, electromagnets have been used for magnetic levitation, as they can be simply controlled via their terminal voltages. This paper, however, studies a levitation system relying on a permanent magnet and a linear servomotor to control the applied magnetic force by changing the distance between the magnet and the levitating object. For the proposed system, which is highly nonlinear, a stabilizing feedback control law is developed using feedback linearization and other control design tools. Then, the closed-loop stability is examined against system parameters such as the size of the levitating object, the viscosity of the medium it moves in, and certain characteristics of the magnet in use. The emphasis here is on understanding the impact of intrinsic servomotor limitations, particularly its finite slew rate (cap on its maximum velocity), on the ability of feedback control to stabilize the closed-loop system. This particular limitation seems to be a major concern in utilizing permanent magnets for noncontact actuation and control. 

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2. 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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3. Magnetohydrodynamic levitation for high-performance flexible pumps

   https://doi.org/10.1073/pnas.2203116119  

   Matia, Yoav; An, Hyeon Seok; Shepherd, Robert F.; Lazarus, Nathan (July 2022, Proceedings of the National Academy of Sciences)

   We use magnetohydrodynamic levitation as a means to create a soft, elastomeric, solenoid-driven pump (ESP). We present a theoretical framework and fabrication of a pump designed to address the unique challenges of soft robotics, maintaining pumping performance under deformation. Using a permanent magnet as a piston and ferrofluid as a liquid seal, we model and construct a deformable displacement pump. The magnet is driven back and forth along the length of a flexible core tube by a series of solenoids made of thin conductive wire. The magnet piston is kept concentric within the tube by Maxwell stresses within the ferrofluid and magnetohydrodynamic levitation, as viscous lift pressure is created due to its forward velocity. The centering of the magnet reduces shear stresses during pumping and improves efficiency. We provide a predictive model and capture the transient nonlinear dynamics of the magnet during operation, leading to a parametric performance curve characterizing the ESP, enabling goal-driven design. In our experimental validation, we report a shut-off pressure of 2 to 8 kPa and run-out flow rate of 50 to 320 mL⋅min −1 , while subject to deformation of its own length scale, drawing a total of 0.17 W. This performance leads to the highest reported duty point (i.e., pressure and flow rate provided under load) for a pump that operates under deformation of its own length scale. We then integrate the pump into an elastomeric chassis and squeeze it through a tortuous pathway while providing continuous fluid pressure and flow rate; the vehicle then emerges at the other end and propels itself swimming. 

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4. MagNet: A Neural Network for Directed Graphs

   Zhang, Xitong; He, Yixuan; Brugnone, Nathan; Perlmutter, Michael; Hirn, Matthew (January 2021, Advances in neural information processing systems)

   Ranzato, M.; Beygelzimer, A.; Dauphin, Y.; Liang, P.S.; Vaughan, J. Wortman (Ed.)

   The prevalence of graph-based data has spurred the rapid development of graph neural networks (GNNs) and related machine learning algorithms. Yet, despite the many datasets naturally modeled as directed graphs, including citation, website, and traffic networks, the vast majority of this research focuses on undirected graphs. In this paper, we propose MagNet, a GNN for directed graphs based on a complex Hermitian matrix known as the magnetic Laplacian. This matrix encodes undirected geometric structure in the magnitude of its entries and directional information in their phase. A charge parameter attunes spectral information to variation among directed cycles. We apply our network to a variety of directed graph node classification and link prediction tasks showing that MagNet performs well on all tasks and that its performance exceeds all other methods on a majority of such tasks. The underlying principles of MagNet are such that it can be adapted to other GNN architectures. 

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5. Novel Design of Six-Phase Spoke-Type Ferrite Permanent Magnet Motor for Electric Truck Application

   https://doi.org/10.3390/en15061997  

   Won, Hoyun; Hong, Yang-Ki; Choi, Minyeong; Platt, Jonathan; Bryant, Briana; Choi, Seungdeog; Li, Shuhui; Yoon, Hwan-Sik; Haskew, Timothy A.; Lee, Jongkook; et al (March 2022, Energies)

   This paper proposes a 300 kW 24-slot/10-pole 6-phase stator-shifted fractional-slot concentrated winding spoke-type ferrite permanent magnet machine for electric truck applications. The proposed motor consists of a stator with dual three-phase windings positioned 75 degrees apart to reduce higher-order MMF harmonic order, and a rotor with an inexpensive and high-resistance ferrite permanent magnet in the spoke configuration. The simulated result of the stator-shifted machine is compared with a fabricated stator-shifted machine, and the results show good agreement with each other. To further reduce the torque ripple from 2.5 to 0.9% while maintaining a high maximum torque of 2980 Nm, circular voids with a diameter of 11 mm are embedded in the rotor. The proposed motor is evaluated for irreversible demagnetization, mechanical and thermal stability, and fault tolerant ability. To assess the proposed motor performance, the electric truck simulation model is constructed using MATLAB/Simulink and used to compare with the reported 12-slot/10-pole rare-earth permanent magnet-based machine. Compared to a previously reported six-phase rare-earth permanent magnet based flat-type machine, the proposed motor can save 4.3 kWh of energy with a USD 2512 lower cost while retaining a similar motor performance. 

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