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Modeling of system motors with flexible component

By Aleš Lebeda

Abstract

This thesis deals with problem of experimental identification using principles of artificial intelligence and development of nonlinear models. It shows how to estimate parameters of nonlinear models and it compares different types of nonlinear models based on analytical analysis which were developed from measured data in simulation and real system motors with flexible component

Topics: nonlinear least square; linearizace; neural networks; gradient-based algorithms; identifikace; nonlinear optimization; neuronové sítě; polynomial models; nelineární optimizace; linearization; identification; gradientní metody; polynomiální modely; nelineární nejmenší čtverce
Publisher: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Year: 2012
OAI identifier: oai:invenio.nusl.cz:219693
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