Controladores regulatórios auto-sintonizados de distúrbios cíclicos baseados em lógica fuzzy

Detalhes bibliográficos
Ano de defesa: 2022
Autor(a) principal: Pereira, Rogerio Passos do Amaral
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal do Espírito Santo
BR
Doutorado em Engenharia Elétrica
Centro Tecnológico
UFES
Programa de Pós-Graduação em Engenharia Elétrica
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://repositorio.ufes.br/handle/10/12213
Resumo: Some industrial processes have intrinsic cyclic disturbances. In these cases, it is natural to use Iterative Learning Control (ILC) or Repetitive Control (RC), or even combinations of these with other controllers, such as the Repetitive GPC (R-GPC), which integrates the RC with the Generalized Predictive Controller (GPC). One of the main weaknesses of these controllers is when the frequency of the periodic signal varies, as there is a gradual loss in its efficiency. Thus, in this PhD Thesis, a Fuzzy Logic based technique is proposed to estimate the total number of samples contained in a periodic disturbance subject to small and unknown frequency variations. Therefore, the Adaptive Fuzzy ILC (AF-ILC) controller and the Adaptive Fuzzy Repetitive GPC (AFR-GPC) controller are proposed here. In the AF-ILC, the proposed Fuzzy Estimator is applied to the ILC controller, whereas, in the AFR-GPC the Fuzzy Estimator is applied to a structure composed of predictive controllers, allowing these controllers to minimize periodic disturbances with frequency changes over time. Before testing, the controllers are tuned offline via genetic algorithm (AG). To adapt these controllers for frequency change variation, the number of disturbance samples is estimated with the system operating in closed loop (self-tuning adaptive controller) using Fuzzy Logic. As a case study, these controllers are tested in computer simulations in a continuous casting plant to compensate for the bulging disturbance present in the mold level control. In addition to the simulations, the controllers are tested in a didactic plant consisting of a resistive-capacitive circuit where periodic disturbances are present, which, although not having the same structure as the casting system, allows demonstrating that the proposed controllers work for a real plant.