principal conclusão deste artigo é de a presença de determinadas distorções no sinal da FBG interrogada podem levar a um desempenho ruim de algoritmos que mostraram bons resultados na literatura em condições mais próximas das ideais.
6.3 Outros
O artigo Sensorless Control of PMSM Using a New Efficient Neural Network Speed Estima- tor(SPERB et al., 2011), publicado na conferência POWERENG 2011, propôs uma estratégia de controle sensorless para motores síncronos de imãs permanentes utilizando uma RNA do tipo FCC. Neste trabalho, a RNA foi treinada para estimar a velocidade do motor utilizando o erro entre as correntes lidas e as correntes estimadas. O método proposto se mostrou útil na sua tarefa, apesar de depender da estimação das correntes por outros métodos.
Programas computacionais foram implementados ao longo do mestrado com o objetivo de prover as ferramentas necessárias para o desenvolvimento do trabalho. Estes programas foram publicados com uma licença de código aberto (GPLv3).
O programa SuperNN (NEGRI, 2010a) é uma biblioteca que implementa o treinamento e execução de RNAs alimentadas adiante com topologias arbitrárias, com suporte a algoritmos de treinamento supervisionado como o iRPROP e o NBN. Também foi implementada uma biblioteca para o treinamento supervisionado de SVMs pelo método KA (NEGRI, 2011a).
As implementações dos métodos de detecção de pico também foram publicadas (NEGRI, 2010b). Neste pacote encontram-se programas que implementam o método do ponto máximo, centroide, ajuste polinomial, ajuste gaussiano, filtro digital e do método proposto por uma RNA do tipo FCC.
A biblioteca cpso (NEGRI, 2011b) foi desenvolvida com o objetivo de implementar o algoritmo genérico de PSO. O programa psofit (NEGRI, 2011c), implementado com a biblioteca cpsorealiza o ajuste dos parâmetros do modelo de Cole por meio de PSO, com suporte à variações do modelo para compensar a presença de artefatos.
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