scholarly journals Minor loop dependence of the magnetic forces and stiffness in a PM-HTS levitation system

AIP Advances ◽  
2017 ◽  
Vol 7 (12) ◽  
pp. 125028
Author(s):  
Yong Yang ◽  
Chengshan Li
1974 ◽  
Vol 3 (5) ◽  
pp. 359-366 ◽  
Author(s):  
H. Hieronymus ◽  
J. Miericke ◽  
F. Pawlitschek ◽  
M. Rudel

2016 ◽  
pp. 4058-4069
Author(s):  
Michael A Persinger

                                Translation of four dimensional axes anywhere within the spatial and temporal boundaries of the universe would require quantitative values from convergence between parameters that reflect these limits. The presence of entanglement and volumetric velocities indicates that the initiating energy for displacement and transposition of axes would be within the upper limit of the rest mass of a single photon which is the same order of magnitude as a macroscopic Hamiltonian of the modified Schrödinger wave function. The representative metaphor is that any local 4-D geometry, rather than displaying restricted movement through Minkowskian space, would instead expand to the total universal space-time volume before re-converging into another location where it would be subject to cause-effect. Within this transient context the contributions from the anisotropic features of entropy and the laws of thermodynamics would be minimal.  The central operation of a fundamental unit of 10-20 J, the hydrogen line frequency, and the Bohr orbital time for ground state electrons would be required for the relocalized manifestation. Similar quantified convergence occurs for the ~1012 parallel states within space per Planck’s time which solve for phase-shift increments where Casimir and magnetic forces intersect.  Experimental support for these interpretations and potential applications is considered. The multiple, convergent solutions of basic universal quantities suggest that translations of spatial axes into adjacent spatial states and the transposition of four dimensional configurations any where and any time within the universe may be accessed but would require alternative perspectives and technologies.


2021 ◽  
Vol 11 (5) ◽  
pp. 2396
Author(s):  
Jong Suk Lim ◽  
Hyung-Woo Lee

This paper presents a method of utilizing a non-contact position sensor for the tilting and movement control of a rotor in a rotary magnetic levitation motor system. This system has been studied with the aim of having a relatively simple and highly clean alternative application compared to the spin coater used in the photoresist coating process in the semiconductor wafer process. To eliminate system wear and dust problems, a shaft-and-bearing-free magnetic levitation motor system was designed and a minimal non-contact position sensor was placed. An algorithm capable of preventing derailment and precise movement control by applying only control without additional mechanical devices to this magnetic levitation system was proposed. The proposed algorithm was verified through simulations and experiments, and the validity of the algorithm was verified by deriving a precision control result suitable for the movement control command in units of 0.1 mm at 50 rpm rotation drive.


2021 ◽  
Vol 11 (6) ◽  
pp. 2535
Author(s):  
Bruno E. Silva ◽  
Ramiro S. Barbosa

In this article, we designed and implemented neural controllers to control a nonlinear and unstable magnetic levitation system composed of an electromagnet and a magnetic disk. The objective was to evaluate the implementation and performance of neural control algorithms in a low-cost hardware. In a first phase, we designed two classical controllers with the objective to provide the training data for the neural controllers. After, we identified several neural models of the levitation system using Nonlinear AutoRegressive eXogenous (NARX)-type neural networks that were used to emulate the forward dynamics of the system. Finally, we designed and implemented three neural control structures: the inverse controller, the internal model controller, and the model reference controller for the control of the levitation system. The neural controllers were tested on a low-cost Arduino control platform through MATLAB/Simulink. The experimental results proved the good performance of the neural controllers.


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