Aplicação de Máquinas de Aprendizado Extremo ao Problema de Identificação de Sistemas Não-Lineares

Renan D. B. Brotto, Levy Boccato, João M. T. Romano

DOI: 10.14209/sbrt.2017.180

Evento: XXXV Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2017)

Keywords: Nonlinear system identification Artificial neural networks Extreme learning machines

Abstract

This work proposes the application of extreme learning machines to the problem of nonlinear system identifi- cation. Such structure constitutes a promissing option because it presents the capability of approximating nonlinear mappings and simplicity in the process of parameter adaptation. The proposed strategy is analyzed in a scenario related to the control system of a pneumatic valve, being compared with two other models based on multilayer perceptron networks. The obtained results show that the ELM is very suitable for the task.

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