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Doctoral Thesis
DOI
https://doi.org/10.11606/T.3.2019.tde-29052019-102550
Document
Author
Full name
André Luiz de Oliveira
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2019
Supervisor
Committee
Sguarezi Filho, Alfeu Joãozinho (President)
Odloak, Darci
Pavani, Ahda Pionkoski Grilo
Pelizari, Ademir
Teixeira, Julio Carlos
Title in Portuguese
Controle preditivo robusto tipo Finite Control Set aplicado ao controle das potências do gerador de indução duplamente alimentado.
Keywords in Portuguese
Controle preditivo
Controle robusto
Energia eólica
Finite control set
Gerador de indução duplamente alimentado
Abstract in Portuguese
Esta tese de doutorado propõe um controlador preditivo robusto tipo finite control set aplicado ao controle das potências do gerador de indução duplamente alimentado. Desta forma, a proposta possui dois membros do vetor tensão predita do rotor, sendo que o primeiro termo calcula a tensão considerando as referências de corrente do rotor e o segundo é projetado considerando os erros devido à estimação dos parâmetros da máquina. Os referidos erros devido a variações de parâmetros são modelados como alterações na corrente do rotor. O vetor de tensão a ser fornecido ao rotor da máquina é selecionado através da minimização de uma função custo. Os resultados obtidos na simulação computacional e em bancada experimental confirmam o desempenho do controlador proposto.
Title in English
Robust predictive Finite Control Set applied to powers control of doubly fed induction induction generator.
Keywords in English
Doubly-fed induction generator
Finite control set
Model predictive control
Robust control
Wind energy
Abstract in English
This Ph.D. thesis proposes a robust predictive controller type finite control set applied to control of the powers at doubly fed induction generator. In this way, the proposal has two members of the predicted voltage vector of the rotor, the first term calculating the voltage considering the rotor references current and the second one is projected considering the errors due to the estimation of the machine parameters. The errors due to variations parameter are modeled as changes in the rotor current. The voltage vector to be supplied to the machine rotor is selected by minimizing a cost function. The results obtained in the computational simulation and experimental bench confirm the performance of the proposed controller.
 
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Publishing Date
2019-05-31
 
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