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The conveyance of steel-plates is one of the potential uses of the magnetic levitation technology in industry. How¬ever, the electromagnetic levitation systems inherently show non¬linear feature and are unstable without an active control. Well-known U-shaped or E-shaped electromagnets cannot provide redundant levitation with multiple degrees of freedom. In this paper, to achieve the full redundant levitation of the steel plate, a quadruple configuration of U shaped electromagnets has been proposed. To resolve the issue of instability and attain more robust levitation, a centralized control algorithm based on a modified PID controller (I PD) is designed for each degree of freedom by using the Manabe canonical polynomial technique. The model of the system is carried out using electromechanical energy conversion princi¬ples and verified by 3-D FEM analysis. An experimental bench is built up to test the system performance under trajectory tracking and external disturbance excitation. The results confirm the effectiveness of the proposed system and the control approach to obtain a full redundant levitation even in case of disturbances. The paper demonstrates the feasibility of the con¬veyance of steel plates by using the quadruple configuration of U-shaped electromagnets and shows the merits of I-PD controller both in stabilization and increased robust levitation.

This paper presents the mechanical vibration and stress analysis of an axial flux permanent magnet (AFPM) motor for a high speed (30000 rev/min) rotor which is vertically suspended by active and hybrid magnetic bearings. In the analysis, a prototype AFPM motor with a double sided rotor and a coreless stator between the rotors are considered. Rotor disks of the motor are constructed of two 10 mm-thick steel disks with 6.35 mm-thick permanent magnets which represent around 70% of the total weight of the machine. Firstly, an analytical solution is carried out to determine natural frequencies of the rotor-shaft system. Then rotor disk thickness was determined based on a rotor axial displacement due to the attractive force between the permanent magnets placed on opposite rotor disks. Finally, 3D finite elements analysis (FEA) are carried out to verify the analytical results.

Along with technological developments and increasing population, people are in need of more energy sources. This need has led researchers to go towards new energy generation methods. One of these methods is hydrokinetic energy generation, which has been studied intensively in recent years. In this study, complete design of a hydrokinetic turbine that converts kinetic energy into mechanical and electrical energy with the most efficiency using tidal water is proposed. Moreover, an undershot water wheel system is designed to gain the least dissipationless conversion of kinetic energy. The design of the hydrokinetic energy generation system is developed considering the environmental and maintenance factors, maximum efficiency and buoyancy. Calculation for the velocity of the turbine is made by using Betz’s law, usually used for wind energy conversion systems. Conversion of obtained mechanical energy from the turbine to electrical energy is supplied by using a proper alternator system.

CBU International Conference on Innovations in Science and Education (CBUIC) -- MAR 23-25, 2016 -- Prague, CZECH REPUBLIC WOS: 000392271000114 In this study, an artificial neural network was developed for estimating Hashimoto's Thyroiditis subgroups. Medical analysis and measurements from 75 patients were used to determine the parameters most effective on disease sub-groups. The study used statistical analyses and an artificial neural network that was trained by the determined parameters. The neural network had four inputs: thyroid stimulating hormone, free thyroxine (fT4), right lobe size (RLS), and RLS2 - fT4(4), and two outputs for three groups: euthyroid, subclinical, and clinical. After training, the network was tested with data collected from 30 patients. Results show that, overall, the neural network estimated the sub-groups with 90% accuracy. Hence, the study showed that determination of Hashimoto's Thyroiditis sub-groups can be made via designed artificial neural network. Central Bohemia University, Unicorn College

In this study, a flexible conveyance system driven by linear motors and hybrid magnets for magnetic levitation is proposed. For modelling purposes, nonlinear analytic models are derived and extended to 3 axis of movement and controlled with those nonlinear equations. For energy efficiency, each pole is controlled with voltage driving zero power levitation method. Since the system only has displacement sensors for feedback, to fully control and understand the systems characteristics and disturbances, all axis are observed by disturbance observer and integrated to controller algorithm for better response and robustness, which is achieved multiplying the disturbance observer's output with system gain and feedforwarded. The proposed system and control algorithms are well confirmed by numerical results.