Estimador neural de velocidade aplicado a um driver de controle escalar do motor de indução trifásico

• Ano de defesa: 2012
• Autor(a) principal: Santos, Tiago Henrique dos
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Cornelio Procopio; Programa de Pós-Graduação em Engenharia Elétrica
• Palavras-chave em Português: Estimulação neural; Motores elétricos de indução; Redes neurais (Computação); Neural stimulation; Electric motors, Induction; Neural networks (Computer science)
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/781

This work proposes an artificial neural network approach to estimate the induction motor speed applied in a closed-loop scalar control. The induction motor has a great importance in many industrial sectors for the robustness and low cost. Thus, when the load coupled to the axis needs speed control, some of the drive and control strategies are based on the estimated axis speed of the motor. The direct measurement of this quantity reduces its robustness, compromises the driver system and control as well as it increases the implementation cost. The propose of this work is to present an alternative methodology for speed estimate of three phase induction motor driven by a voltage source inverter using space vector modulation in the scalar control strategy. Simulation and experimental results are presented to validate the performance of the proposed method under motor load torque and speed reference set point variations, which show very promising.