The nonlinear case
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Model Predictive Control (MPC) refers to a class of algorithms that optimize the future behavior of the plant subject to operational constraints. The merits of the class algorithms include its ability to handle imposed hard constraints on the system and perform on-line optimization. This thesis investigates design and implementation of continuous time model predictive control using Laguerre polynomials and extends the design approaches proposed in to include intermittent predictive control, as well as to include the case of the nonlinear predictive control.
162p 
runthenight07
01-03-2023
9
4
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Research purpose: to build an analytical model representing the cross Kerr nonlinear coefficient of a four-energy quantum system in the inverse Y configuration in the presence of the Doppler effect. Apply the analytical results to the case of 87Rb at room temperature. Studying the ability to control and enhance the cross Kerr nonlinearity according to the parameters of the associated laser field and the temperature of the environment.
26p prisonbreak123
21-05-2021
18
4
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We obtain global well-posedness, scattering, and global L10 spacetime t,x bounds for energy-class solutions to the quintic defocusing Schr¨dinger equao tion in R1+3 , which is energy-critical. In particular, this establishes global existence of classical solutions. Our work extends the results of Bourgain [4] and Grillakis [20], which handled the radial case.
100p dontetvui
17-01-2013
50
6
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Data-Reusing Adaptive Learning Algorithms In this chapter, a class of data-reusing learning algorithms for recurrent neural networks is analysed. This is achieved starting from a case of feedforward neurons, through to the case of networks with feedback, trained with gradient descent learning algorithms. It is shown that the class of data-reusing algorithms outperforms the standard (a priori ) algorithms for nonlinear adaptive filtering in terms of the instantaneous prediction error.
14p doroxon
12-08-2010
100
10
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