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The second step of our computational procedure is to use the measured Q factors and resonant frequencies for TE110 and TE210 modes as input to a combined transverse resonance condition for TE110 and TE210 modes, and solve then the obtained equations using the optimization algorithm.
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Radiative-conductive heat transfer in porous media is usually investigated by decoupling the heat transfer modes and solving the volume-averaged continuum equations using effective transport properties.
The results indicate the proposed method improves the tracking precision and velocity compared with the conventional integral sliding-mode method, and solves the saturation problem compared with existing NTSMC method.
Based on the suggested algorithm the problem of optimizing transfer times of standby elements to the hot standby mode and optimal sequencing of their transfer to the operation mode is formulated and solved.
Moreover, multivariate EMD (MEMD) has been proposed for dealing with multivariate parameters and solving the mode-mixing for adding noise as well.
Using Euler Bernoulli theory, governing equations are derived and solved in every mode.
The governing equations of motion are reduced and solved by assumed mode model.
The observation problem for linear switched systems with unknown inputs is addressed and solved via sliding mode technique.
The approach taken relies on the concept of Sliding Modes to solve the resulting time-varying optimization problem.
This paper presents the application of a special technique which combines neural networks and sliding modes for solving the robust tracking problem in a nuclear reactor when only the input and the output are available.
Backbone curves for the first and second vibration modes are solved numerically by the Gauss Legendre integration method and the shooting method respectively.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com