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Identification and control of power converters by means of neural networks

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5 Author(s)
Leyva, R. ; Dept. d''Eng. Electron.-URV, Escola Tecnica Superior d''Enginyeria, Tarragona, Spain ; Martinez-Salamero, L. ; Jammes, B. ; Marpinard, J.C.
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This paper investigates the use of neural networks for identification and control of power converters. A nonparametric model of a dc-to-dc switching converter implemented by means of a neural network emulator identifies the converter dynamics in cases of uncertainty in the load parameter. A pseudo-linearization control technique resulting in converter regulation and closed-loop linear dynamic behavior is also implemented by means of a neural controller. Simulation results in a PWM boost converter under large-signal operation illustrate both applications This paper investigates the use of neural networks for identification and control of power converters. A nonparametric model of a dc-to-dc switching converter implemented by means of a neural network emulator identifies the converter dynamics in cases of uncertainty in the load parameter. A pseudo-linearization control technique resulting in converter regulation and closed-loop linear dynamic behavior is also implemented by means of a neural controller. Simulation results in a PWM boost converter under large-signal operation illustrate both applications

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Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on  (Volume:44 ,  Issue: 8 )