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Direct adaptive control using feedforward neural networks

By Daniel Oliveira Cajueiro and Elder Moreira Hemerly

Abstract

This paper proposes a new scheme for direct neural adaptive control that works efficiently employing only one neural network, used for simultaneously identifying and controlling the plant. The idea behind this structure of adaptive control is to compensate the control input obtained by a conventional feedback controller. The neural network training process is carried out by using two different techniques: backpropagation and extended Kalman filter algorithm. Additionally, the convergence of the identification error is investigated by Lyapunov's second method. The performance of the proposed scheme is evaluated via simulations and a real time application.<br>Este artigo propõe uma nova estratégia de controle adaptativo direto em que uma única rede neural é usada para simultaneamente identificar e controlar uma planta. A motivação para essa estratégia de controle adaptativo é compensar a entrada de controle gerada por um controlador retroalimentado convencional. O processo de treinamento da rede neural é realizado através de duas técnicas: backpropagation e filtro de Kalman estendido. Adicionalmente, a convergência do erro de identificação é analisada através do segundo método de Lyapunov. O desempenho da estratégia proposta é avaliado através de simulações e uma aplicação em tempo real

Topics: Backpropagation, controle adaptativo, convergência, estabilidade, filtro de Kalman estendido, redes neurais, Adaptive control, backpropagation, convergence, extended Kalman filter, neural networks, stability, LCC:Electronic computers. Computer science, LCC:QA75.5-76.95, LCC:Instruments and machines, LCC:QA71-90, LCC:Mathematics, LCC:QA1-939, LCC:Science, LCC:Q, DOAJ:Computer Science, DOAJ:Technology and Engineering
Publisher: Sociedade Brasileira de Automática
Year: 2003
DOI identifier: 10.1590/S0103-17592003000400002
OAI identifier: oai:doaj.org/article:313df5d7bd304a36a14e6b0ca0e1c8c1
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