Calibration of Nonlinear Variable Loads Based on Manifold Learning

C.H. MURAVCHIK; A. VENERE; M. HURTADO

Mar del Plata

Congreso; XVII Reunión de Trabajo en Procesamiento de la Información y Control (RPIC 2017); 2017

Facultad de Ingeniería - UNMdP

Abstract - In this work, we present a method for calibratingnon-linear variable impedances based on the manifold-learningtechnique. This approach circumvents the dependency on theanalytical model of the device, and works under the assumptionthat the impedance values come from a "black box" controlled bya number of independent parameters. The goal of the calibrationis to recover the unknown control parameters that set theload into the desired impedance states. We tested the proposedprocedure first on a simulated example and then on the prototypepresented in [1] at a frequency of 1575.42 MHz. The results basedon both simulated and real data showed accurate recovery of thecontrol parameters.