Detalhes bibliográficos
| Ano de defesa: |
2017 |
| Autor(a) principal: |
Machado, Madson Cruz
 |
| Orientador(a): |
FONSECA NETO, João Viana da |
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal do Maranhão
|
| Programa de Pós-Graduação: |
PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
|
| Departamento: |
DEPARTAMENTO DE ENGENHARIA DA ELETRICIDADE/CCET
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://tedebc.ufma.br:8080/jspui/handle/tede/1744
|
Resumo: |
The need to increase industrial productivity coupled with quality and low cost requirements has generated a demand for the development of high performance controllers. Motivated by this demand, we presented in this work models, algorithms and a methodology for the online project of high-performance control systems. The models have characteristics of adaptability through adaptive control system architectures. The models developed were based on artificial neural networks of radial basis function type, for the online project of model reference adaptive control systems associated with the of sliding modes control. The algorithms and the embedded system developed for the online project were evaluated for tracking mobile targets, in this case, the solar radiation. The control system has the objective of keeping the surface of the photovoltaic module perpendicular to the solar radiation, in this way the energy generated by the module will be as high as possible. The process consists of a photovoltaic panel coupled in a structure that rotates around an axis parallel to the earth’s surface, positioning the panel in order to capture the highest solar radiation as function of its displacement throughout the day. |
