Controle preditivo baseado em modelo com conjunto de controle finito aplicado a conversores CC-CC

• Ano de defesa: 2022
• Autor(a) principal: Braga, Isadora Nascimento Della-Sávia
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Lavras; Programa de Pós-Graduação em Engenharia de Sistemas e Automação; UFLA; brasil; Departamento de Engenharia
• Palavras-chave em Português: Conversores CC-CC; Finite Control Set - Model Predictive Control ((FCS-MPC); Voltage Regulator - Battery Energy Storage System (VR-BESS); DC-DC converters; Engenharia Elétrica
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/50496

The generation of energy through renewable and distributed sources has numerous advantages. However, due to intermittence and volatility, it is necessary that these systems be associated with energy storage systems or connected to the electrical grid. This work proposes the applica- tion and performance comparison of the FCS-MPC control in face of the choice of different cost functions applied to a scenario of Buck converter and to two different scenarios of Boost con- verter and Voltage Regulator - Battery Energy Storage System (VR-BESS). The first scenario consists on the use of a classical cost function (voltage) and proposes the use of two others: mul- tivariable voltage and electrical current control; And indirect voltage control through a current cost function. In this scenario there are no corrections for the delays caused by non-minimum phase (NMP). In the second scenario, a new minimum phase output is replaced on the voltage cost function, both classical and multivariable. The converters are simulated in Matlab/Simu- link and the results obtained for the Buck converter demonstrate that the indirect control of the output voltage reaches steady-state values very close to the desired value for voltage. In addi- tion, the multivariable cost function presents a balance between the other functions, reducing the error values and keeping the average values closer to the desired ones, when compared to the scenarios where the control of the variables is done indirectly. For the Boost and VR-BESS converters, the results show that the use of the multivariable cost function alone does not solve the optimization problem caused by the non-minimum phase characteristic. However, when the system is indirectly controlled by current, or when operating with NMP corrections, the FCS-MPC is able to optimize the output with low steady-state errors. In addition, the use of the multivariable cost function with correction reduces steady-state oscillations and mean errors.