Controle preditivo aplicado às malhas de corrente e velocidade de um sistema de acionamento com motor de relutância variável

Detalhes bibliográficos
Ano de defesa: 2013
Autor(a) principal: Silva, Wellington Assunção da
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/5014
Resumo: The Switched Reluctance Machine (SRM) is increasingly drawing the industry and academic community attention. This is due to the increasing development of power electronics and in the microprocessors field in recent years, allowing the advancement of other drive systems such as with SRM. The competitiveness of the SRM is justified by its low cost of production and maintenance, high power density, robustness and reliability. This dissertation proposes a robust control scheme based on a Generalized Predictive Controller (GPC) belonging to the Model Predictive Controller (MPC) Family applied to current and speed loops of a drive system with SRM. The proposed controller, as well as traditional controllers used in this type of system such as the controller and PID controller by hysteresis are applied in order to provide means of comparison of experimental results. The structure of the controller is based on the design of a filter to allow a rapid response, disturbance rejection, noise attenuation and robustness with a low computational cost. The proposed controller was implemented and the results compared with traditional controllers and analyzed quantitatively by performance indexes. The control routines were implemented using a DSP from Texas Instruments (TMS320F28335), and their main characteristics were indicated. The algorithm’s control software is outlined. The work made use of bench research SRM Robotic’s and Automation Group Laboratory.