Utilização de filtro neural adaptativo para eliminar níveis de CC na estimação do conjugado eletromagnético em motores de indução trifásico

• Ano de defesa: 2012
• Autor(a) principal: Linden Filho, Haeckel Van Der
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraí­ba; BR; Engenharia Mecânica; Programa de Pós-Graduação em Engenharia Mecânica; UFPB
• Palavras-chave em Português: Filtro adaptativo; Estimação de fluxo; Motor de indução; Estimação do conjugado; Adaptive filter; Flux estimation; Induction engine; Torque estimation; ENGENHARIAS::ENGENHARIA MECANICA
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/tede/5329

This work presents a study on the application of an ADALINE neural network acting as a notch filter applied to the estimation of the stator flux, in order to obtain the resulting electromagnetic torque of three-phase induction motors (MIT). The estimation of the stator flux was performed by means of the voltage model of the induction machine, in which a integrator is directly applied over the stator counter electromotive force. The ADALINE neural network adaptive filter is employed in this research with the purpose of eliminating existing CC levels, which are present due to the problem of the initial values of the integrator and in the voltage and current measurements. Simulated and experimental results are presented to validate the proposed strategy. The algorithm used in the ADALINE adaptive neural filter simulations was created on the MATLABTM language, and the algorithm used for both the simulations and the laboratory experiments to estimate the flux and the torque was created in the C/C++ language. The hardware used to confirm the effectiveness of the proposed method is based on the Texas Instruments DSP TMS320F28335 platform, along with and induction motor manufactured by WEG, model W21 High Efficiency